https://github.com/lixus7/Time-Series-Works-Conferences

Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
https://github.com/lixus7/Time-Series-Works-Conferences
accident-detection anomaly-detection deep-learning demand-forecasting location multivariate-timeseries paper-list probabilistic-models spatio-temporal spatio-temporal-data spatio-temporal-modeling spatio-temporal-prediction time-series time-series-forecasting time-series-imputation time-series-prediction traffic-prediction travel-time-prediction
Last synced: 18 days ago
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Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
Host: GitHub
URL: https://github.com/lixus7/Time-Series-Works-Conferences
Owner: lixus7
License: mit
Created: 2022-03-24T06:59:12.000Z (about 3 years ago)
Default Branch: main
Last Pushed: 2025-03-06T06:18:59.000Z (2 months ago)
Last Synced: 2025-03-06T07:35:07.264Z (2 months ago)
Topics: accident-detection, anomaly-detection, deep-learning, demand-forecasting, location, multivariate-timeseries, paper-list, probabilistic-models, spatio-temporal, spatio-temporal-data, spatio-temporal-modeling, spatio-temporal-prediction, time-series, time-series-forecasting, time-series-imputation, time-series-prediction, traffic-prediction, travel-time-prediction
Homepage:
Size: 4.14 MB
Stars: 869
Watchers: 23
Forks: 92
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: license
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README

        # Time-Series Works and Conferences

# Backlog (To do): KDD 2025, ...

**Visit our [GitHub Page](https://lixus7.github.io/Time-Series-Works-Conferences/) for a better view.**

Click here to jump to the Conferences page with more conference information.

or [AI ML Summary Github](https://github.com/Lionelsy/Conference-Accepted-Paper-List)

Some other nice time-series repositories:

[xiyuanzh/time-series-papers](https://github.com/xiyuanzh/time-series-papers)

[qingsongedu/awesome-AI-for-time-series-papers](https://github.com/qingsongedu/awesome-AI-for-time-series-papers)

[xuehaouwa/Awesome-Trajectory-Prediction](https://github.com/xuehaouwa/Awesome-Trajectory-Prediction)

[My Time-series Repo-Star List](https://github.com/stars/lixus7/lists/time-series-list)



      

      

      



> I have a strong interest in time-series research. Welcome to contact me for discussions and collaborative efforts.


 I am currently pursuing a doctoral degree in CSE of UNSW, Sydney, under the supervision of Prof. [Flora Salim](https://scholar.google.com.hk/citations?user=Yz35RSYAAAAJ&hl=zh-CN&oi=ao) and [Hao Xue](https://scholar.google.com.hk/citations?user=KwhLl7IAAAAJ&hl=zh-CN&oi=ao). I got the master degree under the supervision of Prof. [Xuan Song](https://scholar.google.com.hk/citations?user=_qCSLpMAAAAJ&hl=zh-CN&oi=ao), [Quanjun Chen](https://scholar.google.com.hk/citations?user=_PKwzTwAAAAJ&hl=zh-CN) and [Renhe Jiang](https://scholar.google.com.hk/citations?user=Yo2lwasAAAAJ&hl=zh-CN&oi=ao).

The task section has been completed and we will continue to update the methodology section. If you encounter any missing resources (papers/code) or errors, please don't hesitate to open an issue or make a pull request. Additionally, if you're interested in collaborating on this work, please feel free to contact me.

All papers are organized by task and methodology, including those not included in this GitHub repository, and are available for everyone to use on OneDrive and Google Drive (VPN required). 

[OneDrive](https://1drv.ms/u/s!Au2cJRs-_u93lDbLrSDkDy8htv2V?e=ftuaXd)

 

[Google Drive](https://drive.google.com/drive/folders/17bILWdDxUrufRp3yilYfoU5VKywwS1g6?usp=sharing)

To reduce repetition, some data are in abbreviated form. Some terms may not represent general interpretations and apply only to this repository.

|Full Name | Abbreviation|

|:--|:--|

| Adaptive GNN                       |  AGNN   |

| Attention                          |  Attn   |  

| AutoRegression(RNN,GRU,LSTM)       |  AR     |

| Controlled Differential Equations  |  CDE    |  

| Contrastive Learning               |  CL     |

| Encoder Decoder                    |  EncDec |  

| Ensemble                           |  Ens    |

| Feature Decomposed                 |  FeaD   |

| Federated   Learning               |  FL     |  

| Generative Adversarial Network     |  GAN    |

|  Graph Convolutional Network       |  GCN    |   

| Hour, Day, Week, Month, etc        |  HA     |

| Heterogeneous GNN                  |  HGNN   |

| Multiple Graph                     |  MGNN   |

| Memory                             |  Mem    |   

| Meta Learning                      |  MetaL  |   

| MultiTask                          |  MulT   |     

| Network Architechture Search       |  NAS    |  

| Ordinary Differential Equations    |  ODE    |

| Statistic                          |  Stat   |

| TCN (WaveNet)                      |  TCN    |   

| Temporal Graph Network             |  TGN    |   

| Transformer                        |  Trans  |  

| Transfer Learning                  |  TransL |    

| Variational Auto-Encoder           |  VAE    |

# Recent Time Series Works Grouped by Task

- Multivariable Time Series Forecasting

- Multivariable Probabilistic Time Series Forecasting

- Time Series Imputation

- Time Series Anomaly Detection

- Demand Prediction

- Time Series Generation

- Travel Time Estimation

- Traffic Location Prediction

- Event Prediction

- Stock Prediction

- Other Forecasting

  

# [Multivariable Time Series Forecasting](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums:100+ |  |   |   |   |    |

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    SSCNN | [Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting](https://proceedings.neurips.cc/paper_files/paper/2024/hash/7b122d0a0dcb1a86ffa25ccba154652b-Abstract-Conference.html) | [Pytorch](https://github.com/JLDeng/SSCNN)  
![Stars](https://img.shields.io/github/stars/JLDeng/SSCNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JLDeng/SSCNN?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |     | [Are Language Models Actually Useful for Time Series Forecasting?](https://openreview.net/forum?id=54NSHO0lFe) | [Pytorch](https://github.com/BennyTMT/LLMsForTimeSeries)  
![Stars](https://img.shields.io/github/stars/BennyTMT/LLMsForTimeSeries?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BennyTMT/LLMsForTimeSeries?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    PGN | [PGN: The RNN's New Successor is Effective for Long-Range Time Series Forecasting](https://openreview.net/forum?id=ypEamFKu2O&noteId=jpzTU4OIxe) | [Pytorch](https://github.com/Water2sea/TPGN)  
![Stars](https://img.shields.io/github/stars/Water2sea/TPGN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Water2sea/TPGN?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    CATS | [Are Self-Attentions Effective for Time Series Forecasting?](https://openreview.net/forum?id=iN43sJoib7&noteId=VrwF0T4VGH) | [Pytorch](https://github.com/dongbeank/CATS)  
![Stars](https://img.shields.io/github/stars/dongbeank/CATS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/dongbeank/CATS?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Attraos | [Attractor Memory for Long-Term Time Series Forecasting: A Chaos Perspective](https://openreview.net/forum?id=fEYHZzN7kX) | [Pytorch](https://github.com/CityMind-Lab/NeurIPS24-Attraos)  
![Stars](https://img.shields.io/github/stars/CityMind-Lab/NeurIPS24-Attraos?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CityMind-Lab/NeurIPS24-Attraos?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Time-FFM | [Time-FFM: Towards LM-Empowered Federated Foundation Model for Time Series Forecasting](https://openreview.net/forum?id=HS0faHRhWD) | [Pytorch](https://github.com/yuppielqx/Time-FFM)  
![Stars](https://img.shields.io/github/stars/yuppielqx/Time-FFM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yuppielqx/Time-FFM?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Chimera | [Chimera: Effectively Modeling Multivariate Time Series with 2-Dimensional State Space Models](https://openreview.net/forum?id=ncYGjx2vnE) | [Pytorch](https://github.com/ABehrouz/Chimera)  
![Stars](https://img.shields.io/github/stars/ABehrouz/Chimera?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ABehrouz/Chimera?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    TimeXer | [TimeXer: Empowering Transformers for Time Series Forecasting with Exogenous Variables](https://openreview.net/forum?id=INAeUQ04lT) | [Pytorch](https://github.com/thuml/TimeXer)  
![Stars](https://img.shields.io/github/stars/thuml/TimeXer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/TimeXer?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    MiTSformer| [Addressing Spatial-Temporal Heterogeneity: General Mixed Time Series Analysis via Latent Continuity Recovery and Alignment](https://openreview.net/forum?id=EMV8nIDZJn) | [Pytorch](https://github.com/chunhuiz/MiTSformer)  
![Stars](https://img.shields.io/github/stars/chunhuiz/MiTSformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chunhuiz/MiTSformer?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    TTMs| [Tiny Time Mixers (TTMs): Fast Pre-trained Models for Enhanced Zero/Few-Shot Forecasting of Multivariate Time Series](https://openreview.net/forum?id=3O5YCEWETq) | [Pytorch](https://github.com/ibm-granite/granite-tsfm)  
![Stars](https://img.shields.io/github/stars/ibm-granite/granite-tsfm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ibm-granite/granite-tsfm?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Sumba| [Structured Matrix Basis for Multivariate Time Series Forecasting with Interpretable Dynamics](https://openreview.net/forum?id=co7DsOwcop) | [Pytorch](https://github.com/chenxiaodanhit/Sumba)  
![Stars](https://img.shields.io/github/stars/chenxiaodanhit/Sumba?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chenxiaodanhit/Sumba?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Peri-midFormer | [Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis](https://openreview.net/forum?id=5iUxMVJVEV) | [Pytorch](https://github.com/WuQiangXDU/Peri-midFormer)  
![Stars](https://img.shields.io/github/stars/WuQiangXDU/Peri-midFormer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/WuQiangXDU/Peri-midFormer?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Ada-MSHyper | [Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting](https://openreview.net/forum?id=RNbrIQ0se8) | [Pytorch](https://github.com/shangzongjiang/Ada-MSHyper)  
![Stars](https://img.shields.io/github/stars/shangzongjiang/Ada-MSHyper?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/shangzongjiang/Ada-MSHyper?color=critical&style=social)  | NIPS 2024

| Multivariable | ...  |    LPTM | [Large Pre-trained time series models for cross-domain Time series analysis tasks](https://openreview.net/forum?id=vMMzjCr5Zj) | [Pytorch](https://github.com/AdityaLab/LPTM)  
![Stars](https://img.shields.io/github/stars/AdityaLab/LPTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AdityaLab/LPTM?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    CCM | [From Similarity to Superiority: Channel Clustering for Time Series Forecasting](https://openreview.net/forum?id=MDgn9aazo0) | [Pytorch](https://github.com/Graph-and-Geometric-Learning/TimeSeriesCCM)  
![Stars](https://img.shields.io/github/stars/Graph-and-Geometric-Learning/TimeSeriesCCM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Graph-and-Geometric-Learning/TimeSeriesCCM?color=critical&style=social)  | NIPS 2024

| Add News |  Electricity 
 Exchange  
 Traffic 
 Bitcoin  |     | [From News to Forecast: Integrating Event Analysis in LLM-Based Time Series Forecasting with Reflection](https://openreview.net/forum?id=DpByqSbdhI) | [Pytorch](https://github.com/ameliawong1996/From_News_to_Forecast)  
![Stars](https://img.shields.io/github/stars/ameliawong1996/From_News_to_Forecast?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ameliawong1996/From_News_to_Forecast?color=critical&style=social)  | NIPS 2024

| Multivariable |  ImageBind 
 IMU2CLIP  
 IMUGPT 
 HARGPT 
 LLaVA |    UniMTS | [UniMTS: Unified Pre-training for Motion Time Series](https://openreview.net/forum?id=DpByqSbdhI) | [Pytorch](https://github.com/xiyuanzh/UniMTS)  
![Stars](https://img.shields.io/github/stars/xiyuanzh/UniMTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/xiyuanzh/UniMTS?color=critical&style=social)  | NIPS 2024

| Attack |  PEMS03 
 PEMS04  
 PEMS08 
 Weather 
 ETTm1 |    BackTime | [BackTime: Backdoor Attacks on Multivariate Time Series Forecasting](https://openreview.net/forum?id=y8HUXkwAOg) | [Pytorch](https://github.com/xiaolin-cs/BackTime)  
![Stars](https://img.shields.io/github/stars/xiaolin-cs/BackTime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/xiaolin-cs/BackTime?color=critical&style=social)  | NIPS 2024

| Less data |  Electricity 
 Solar  
 Traffic 
 PEMS-BAY 
 METR-LA |    ChronoEpilogi | [ChronoEpilogi: Scalable Time Series Selection with Multiple Solutions](https://openreview.net/forum?id=y8HUXkwAOg) | [Pytorch](https://github.com/ev07/ChronoEpilogi)  
![Stars](https://img.shields.io/github/stars/ev07/ChronoEpilogi?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ev07/ChronoEpilogi?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    FAN | [Frequency Adaptive Normalization For Non-stationary Time Series Forecasting](https://openreview.net/forum?id=T0axIflVDD) | [Pytorch](https://github.com/wayne155/FAN)  
![Stars](https://img.shields.io/github/stars/wayne155/FAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wayne155/FAN?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    GLAFF | [Rethinking the Power of Timestamps for Robust Time Series Forecasting: A Global-Local Fusion Perspective](https://openreview.net/forum?id=EY2agT920S) | [Pytorch](https://github.com/ForestsKing/GLAFF)  
![Stars](https://img.shields.io/github/stars/ForestsKing/GLAFF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ForestsKing/GLAFF?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    FilterNet | [FilterNet: Harnessing Frequency Filters for Time Series Forecasting](https://openreview.net/forum?id=ugL2D9idAD) | [Pytorch](https://github.com/aikunyi/FilterNet)  
![Stars](https://img.shields.io/github/stars/aikunyi/FilterNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/aikunyi/FilterNet?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    CycleNet | [CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns](https://openreview.net/forum?id=clBiQUgj4w) | [Pytorch](https://github.com/ACAT-SCUT/CycleNet)  
![Stars](https://img.shields.io/github/stars/ACAT-SCUT/CycleNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ACAT-SCUT/CycleNet?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    RATD | [Retrieval-Augmented Diffusion Models for Time Series Forecasting](https://openreview.net/forum?id=dRJJt0Ji48&noteId=8wGyyvVUNr) | [Pytorch](https://github.com/stanliu96/RATD)  
![Stars](https://img.shields.io/github/stars/stanliu96/RATD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/stanliu96/RATD?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    DDN | [DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting](https://openreview.net/forum?id=RVZfra6sZo) | [Pytorch](https://github.com/Hank0626/DDN)  
![Stars](https://img.shields.io/github/stars/Hank0626/DDN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Hank0626/DDN?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    FBM | [Rethinking Fourier Transform from A Basis Functions Perspective for Long-term Time Series Forecasting](https://openreview.net/forum?id=BAfKBkr8IP) | [Pytorch](https://github.com/runze1223/Fourier-Basis-Mapping)  
![Stars](https://img.shields.io/github/stars/runze1223/Fourier-Basis-Mapping?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/runze1223/Fourier-Basis-Mapping?color=critical&style=social)  | NIPS 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    BSA | [Introducing Spectral Attention for Long-Range Dependency in Time Series Forecasting](https://openreview.net/forum?id=dxyNVEBQMp) | [Pytorch](https://github.com/DJLee1208/BSA_2024)  
![Stars](https://img.shields.io/github/stars/DJLee1208/BSA_2024?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DJLee1208/BSA_2024?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    DeformableTST | [DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching](https://openreview.net/forum?id=B1Iq1EOiVU) | [Pytorch](https://github.com/luodhhh/DeformableTST)  
![Stars](https://img.shields.io/github/stars/luodhhh/DeformableTST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/luodhhh/DeformableTST?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    SOFTS | [SOFTS: Efficient Multivariate Time Series Forecasting with Series-Core Fusion](https://openreview.net/forum?id=89AUi5L1uA) | [Pytorch](https://github.com/Secilia-Cxy/SOFTS)  
![Stars](https://img.shields.io/github/stars/Secilia-Cxy/SOFTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Secilia-Cxy/SOFTS?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |     | [Scaling Law for Time Series Forecasting](https://openreview.net/forum?id=Cr2jEHJB9q) | [Pytorch](https://github.com/JingzheShi/ScalingLawForTimeSeriesForecasting)  
![Stars](https://img.shields.io/github/stars/JingzheShi/ScalingLawForTimeSeriesForecasting?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JingzheShi/ScalingLawForTimeSeriesForecasting?color=critical&style=social)  | NIPS 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    AutoTimes | [AutoTimes: Autoregressive Time Series Forecasters via Large Language Models](https://openreview.net/forum?id=HS0faHRhWD) | [Pytorch](https://github.com/thuml/AutoTimes)  
![Stars](https://img.shields.io/github/stars/thuml/AutoTimes?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/AutoTimes?color=critical&style=social)  | NIPS 2024

| Multi Task |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    UniTS | [UniTS: A Unified Multi-Task Time Series Model](https://openreview.net/forum?id=nBOdYBptWW) | [Pytorch](https://github.com/mims-harvard/UniTS)  
![Stars](https://img.shields.io/github/stars/mims-harvard/UniTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mims-harvard/UniTS?color=critical&style=social)  | NIPS 2024

| Foundation TS | ...   |    MOMENT | [MOMENT: A Family of Open Time-series Foundation Models](https://icml.cc/virtual/2024/poster/34530) | [Pytorch](https://github.com/moment-timeseries-foundation-model/moment)  
![Stars](https://img.shields.io/github/stars/moment-timeseries-foundation-model/moment?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/moment-timeseries-foundation-model/moment?color=critical&style=social)  | ICML 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    OSL | [An Analysis of Linear Time Series Forecasting Models](https://icml.cc/virtual/2024/poster/32697) | [Pytorch](https://github.com/sir-lab/linear-forecasting)  
![Stars](https://img.shields.io/github/stars/sir-lab/linear-forecasting?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sir-lab/linear-forecasting?color=critical&style=social)  | ICML 2024

| Six |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    UP2ME | [UP2ME: Univariate Pre-training to Multivariate Fine-tuning as a General-purpose Framework for Multivariate Time Series Analysis](https://icml.cc/virtual/2024/poster/33686) | [Pytorch](https://github.com/Thinklab-SJTU/UP2ME)  
![Stars](https://img.shields.io/github/stars/Thinklab-SJTU/UP2ME?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Thinklab-SJTU/UP2ME?color=critical&style=social)  | ICML 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    SparseTSF | [SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters](https://openreview.net/forum?id=54NSHO0lFe) | [Pytorch](https://github.com/lss-1138/SparseTSF)  
![Stars](https://img.shields.io/github/stars/lss-1138/SparseTSF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/lss-1138/SparseTSF?color=critical&style=social)  | ICML 2024

| Multivariable |  Electricity  
 PEMSD7M 
 BikeNYC 
 [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    SCNN | [Disentangling Structured Components: Towards Adaptive, Interpretable and Scalable Time Series Forecasting](https://ieeexplore.ieee.org/document/10457027) | [Pytorch](https://github.com/JLDeng/SCNN)  
![Stars](https://img.shields.io/github/stars/JLDeng/SCNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JLDeng/SCNN?color=critical&style=social)  | TKDE 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    iTransformer | [iTransformer: Inverted Transformers Are Effective for Time Series Forecasting](https://openreview.net/forum?id=JePfAI8fah) | [Pytorch](https://github.com/thuml/iTransformer)  
![Stars](https://img.shields.io/github/stars/thuml/iTransformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/iTransformer?color=critical&style=social)  | ICLR 2024

| Multivariable | NorPool  
 Caiso  
 Traffic  
 Electricity   
 Weather  
 Exchange   
     ETT       
 Wind  |    mr-Diff | [Multi-Resolution Diffusion Models for Time Series Forecasting](https://openreview.net/forum?id=mmjnr0G8ZY) | None  | ICLR 2024

| Multivariable | ETT     
 Electricity   
 Weather 
 Traffic  
 Exchange  
 ILI  |    ModernTCN | [Multi-Resolution Diffusion Models for Time Series Forecasting](https://openreview.net/forum?id=vpJMJerXHU) | [Pytorch](https://github.com/luodhhh/ModernTCN)  
![Stars](https://img.shields.io/github/stars/luodhhh/ModernTCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/luodhhh/ModernTCN?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    Time-LLM | [Time-LLM: Time Series Forecasting by Reprogramming Large Language Models](https://openreview.net/forum?id=Unb5CVPtae) | [Pytorch](https://github.com/KimMeen/Time-LLM)  
![Stars](https://img.shields.io/github/stars/KimMeen/Time-LLM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/KimMeen/Time-LLM?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |   TEMPO | [TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecasting](https://openreview.net/forum?id=YH5w12OUuU) | [Pytorch](https://github.com/DC-research/TEMPO)  
![Stars](https://img.shields.io/github/stars/DC-research/TEMPO?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DC-research/TEMPO?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |   CARD | [CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting](https://openreview.net/forum?id=MJksrOhurE) | [Pytorch](https://github.com/wxie9/CARD)  
![Stars](https://img.shields.io/github/stars/wxie9/CARD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wxie9/CARD?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |  ARM | [ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning](https://openreview.net/forum?id=JWpwDdVbaM) | None | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |  DAM | [DAM: Towards a Foundation Model for Forecasting](https://openreview.net/forum?id=4NhMhElWqP) | [None](https://openreview.net/attachment?id=4NhMhElWqP&name=supplementary_material) | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  
 PEMS3478 |  TimeMixer | [TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting](https://openreview.net/forum?id=7oLshfEIC2) | [Pytorch](https://github.com/kwuking/TimeMixer)  
![Stars](https://img.shields.io/github/stars/kwuking/TimeMixer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/kwuking/TimeMixer?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |  PDF  | [Periodicity Decoupling Framework for Long-term Series Forecasting](https://openreview.net/forum?id=dp27P5HBBt) | [Pytorch](https://github.com/Hank0626/PDF)  
![Stars](https://img.shields.io/github/stars/Hank0626/PDF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Hank0626/PDF?color=critical&style=social)  | ICLR 2024

| Multivariable 
 Missing Value|  METR-LA  
 Electricity  
 PEMS 
 ETT 
 BeijingAir|  BiTGraph  | [Biased Temporal Convolution Graph Network for Time Series Forecasting with Missing Values](https://openreview.net/forum?id=O9nZCwdGcG) | [Pytorch](https://github.com/chenxiaodanhit/BiTGraph)  
![Stars](https://img.shields.io/github/stars/chenxiaodanhit/BiTGraph?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chenxiaodanhit/BiTGraph?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)  
 PEMS08 |  LIFT  | [Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators](https://openreview.net/forum?id=JiTVtCUOpS) | [Pytorch](https://github.com/SJTU-Quant/LIFT)  
![Stars](https://img.shields.io/github/stars/SJTU-Quant/LIFT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SJTU-Quant/LIFT?color=critical&style=social)  | ICLR 2024

| Multivariable | ETT     
 Weather 
 ILI  
 Traffic   |    STanHop | [STanHop: Sparse Tandem Hopfield Model for Memory-Enhanced Time Series Prediction](https://openreview.net/forum?id=6iwg437CZs) | [Pytorch](https://github.com/MAGICS-LAB/STanHop)  
![Stars](https://img.shields.io/github/stars/MAGICS-LAB/STanHop?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/MAGICS-LAB/STanHop?color=critical&style=social)  | ICLR 2024

| Multivariable | ETT     
 Weather  
 Electricity  
 Traffic 
 ILI    
 CloudCluster |    Pathformer | [Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting](https://openreview.net/forum?id=vpJMJerXHU) | [Pytorch](https://github.com/decisionintelligence/pathformer)  
![Stars](https://img.shields.io/github/stars/decisionintelligence/pathformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/decisionintelligence/pathformer?color=critical&style=social)  | ICLR 2024

| Multivariable |   [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    pits | [Learning to Embed Time Series Patches Independently](https://openreview.net/forum?id=vpJMJerXHU) | [Pytorch](https://github.com/seunghan96/pits)  
![Stars](https://img.shields.io/github/stars/seunghan96/pits?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/seunghan96/pits?color=critical&style=social)  | ICLR 2024

| Multivariable | ETT    
 Weather  
 Electricity  
 Traffic   |    FITS | [FITS: Modeling Time Series with 10k Parameters](https://openreview.net/forum?id=bWcnvZ3qMb) | [Pytorch](https://github.com/VEWOXIC/FITS)  
![Stars](https://img.shields.io/github/stars/VEWOXIC/FITS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/VEWOXIC/FITS?color=critical&style=social)  | ICLR 2024

| Multivariable | ETT  
 Electricity    
 Weather  
 Lora   |    AutoTCL | [Parametric Augmentation for Time Series Contrastive Learnin](https://openreview.net/forum?id=EIPLdFy3vp) | [Pytorch](https://github.com/AslanDing/AutoTCL)  
![Stars](https://img.shields.io/github/stars/AslanDing/AutoTCL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AslanDing/AutoTCL?color=critical&style=social)  | ICLR 2024

| Multivariable | ETT    
 Exchange  
 ILI   |    GLIP | [Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction](https://openreview.net/forum?id=aFWUY3E7ws) | [Pytorch](https://openreview.net/attachment?id=aFWUY3E7ws&name=supplementary_material)   | ICLR 2024

| Multivariable | [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    Fredformer | [Fredformer: Frequency Debiased Transformer for Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3637528.3671855) |  [Pytorch](https://github.com/chenzRG/Fredformer)  
![Stars](https://img.shields.io/github/stars/chenzRG/Fredformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chenzRG/Fredformer?color=critical&style=social)  | KDD 2024

| Multivariable | [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    GPHT | [Generative Pretrained Hierarchical Transformer for Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3637528.3671855) |  [Pytorch](https://github.com/icantnamemyself/GPHT)  
![Stars](https://img.shields.io/github/stars/icantnamemyself/GPHT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/icantnamemyself/GPHT?color=critical&style=social)  | KDD 2024

| Multivariable | [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    FRNet | [FRNet: Frequency-based Rotation Network for Long-term Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3637528.3671713) |  [Pytorch](https://github.com/SiriZhang45/FRNet)  
![Stars](https://img.shields.io/github/stars/SiriZhang45/FRNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SiriZhang45/FRNet?color=critical&style=social)  | KDD 2024

| Missing MTS | METR-LA 
 PEMS-BAY 
 PEMS04 
 PEMS08 
 China AQI   |    GinAR | [GinAR: An End-To-End Multivariate Time Series Forecasting Model Suitable for Variable Missing](https://dl.acm.org/doi/abs/10.1145/3637528.3672055) |  [Pytorch](https://github.com/GestaltCogTeam/GinAR)  
![Stars](https://img.shields.io/github/stars/GestaltCogTeam/GinAR?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GestaltCogTeam/GinAR?color=critical&style=social)  | KDD 2024

| Multivariable | METR-LA 
 PEMS-BAY 
 PEMS04 
 
  PEMS07  PEMS08   |    HimNet | [Heterogeneity-Informed Meta-Parameter Learning for Spatiotemporal Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3637528.3671961) |  [Pytorch](https://github.com/XDZhelheim/HimNet)  
![Stars](https://img.shields.io/github/stars/XDZhelheim/HimNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/XDZhelheim/HimNet?color=critical&style=social)  | KDD 2024

| Multivariable | [TimesNet_data](https://github.com/thuml/Time-Series-Library)  |    CDS | [Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift](https://dl.acm.org/doi/abs/10.1145/3637528.3671926) |  [Pytorch](https://github.com/HALF111/calibration_CDS)  
![Stars](https://img.shields.io/github/stars/HALF111/calibration_CDS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HALF111/calibration_CDS?color=critical&style=social)  | KDD 2024

| Foundation 
 Traffic | TaxiBJ 
 Crawd 
 BikeNYC 
 Cellular 
 TDrive 
 TrafficSH |    UniST | [UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction](https://dl.acm.org/doi/abs/10.1145/3637528.3671662) |  [Pytorch](https://github.com/tsinghua-fib-lab/UniST)  
![Stars](https://img.shields.io/github/stars/tsinghua-fib-lab/UniST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tsinghua-fib-lab/UniST?color=critical&style=social)  | KDD 2024

| Early 
 Traffic | METR-LA 
 EMS 
 NYPD  |    STEMO | [STEMO: Early Spatio-temporal Forecasting with Multi-Objective Reinforcement Learning](https://dl.acm.org/doi/abs/10.1145/3637528.3671922) |  [Pytorch](https://github.com/coco0106/MO-STEP)  
![Stars](https://img.shields.io/github/stars/coco0106/MO-STEP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/coco0106/MO-STEP?color=critical&style=social)  | KDD 2024

| New nodes 
 Traffic | Large-ST |    STONE | [STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts](https://dl.acm.org/doi/abs/10.1145/3637528.3671680) |  [Pytorch](https://github.com/PoorOtterBob/STONE-KDD-2024)  
![Stars](https://img.shields.io/github/stars/PoorOtterBob/STONE-KDD-2024?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/PoorOtterBob/STONE-KDD-2024?color=critical&style=social)  | KDD 2024

| Irregular 
 Traffic | Zhuzhou 
 Baoding |    Aseer | [Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks](https://dl.acm.org/doi/abs/10.1145/3637528.3671665) |  [Pytorch](https://github.com/usail-hkust/ASeer)  
![Stars](https://img.shields.io/github/stars/usail-hkust/ASeer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/usail-hkust/ASeer?color=critical&style=social)  | KDD 2024

| Multivariable | Stock 
 Exchange 
 Weather   |    CONTIME | [Addressing Prediction Delays in Time Series Forecasting: A Continuous GRU Approach with Derivative Regularization](https://dl.acm.org/doi/abs/10.1145/3637528.3671969) |  [Pytorch](https://github.com/sheoyon-jhin/CONTIME)  
![Stars](https://img.shields.io/github/stars/sheoyon-jhin/CONTIME?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sheoyon-jhin/CONTIME?color=critical&style=social)  | KDD 2024

| Multivariable | PEMS07 
 Large-ST  |    GWT | [Pre-Training Identification of Graph Winning Tickets in Adaptive Spatial-Temporal Graph Neural Networks](https://dl.acm.org/doi/abs/10.1145/3637528.3671912) |  [Pytorch](https://anonymous.4open.science/r/paper-1430)  | KDD 2024

| Large Scale   | Large-ST  |    RPMixer | [RPMixer: Shaking Up Time Series Forecasting with Random Projections for Large Spatial-Temporal Data](https://dl.acm.org/doi/abs/10.1145/3637528.3671881) |  [Pytorch](https://sites.google.com/view/rpmixer)   | KDD 2024

| Demand Supply 
 Prediction | Shanghai 
 Zhengzhou   |    MulSTE | [MulSTE: A Multi-view Spatio-temporal Learning Framework with Heterogeneous Event Fusion for Demand-supply Prediction](https://dl.acm.org/doi/abs/10.1145/3637528.3672030) |  [Pytorch](https://github.com/mulste-kdd2024/MulSTE)  
![Stars](https://img.shields.io/github/stars/mulste-kdd2024/MulSTE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mulste-kdd2024/MulSTE?color=critical&style=social)  | KDD 2024

| Multivariable | 108s   |    AutoXPCR | [AutoXPCR: Automated Multi-Objective Model Selection for Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3637528.3672057) |  [TF](https://github.com/raphischer/xpcr)  
![Stars](https://img.shields.io/github/stars/raphischer/xpcr?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/raphischer/xpcr?color=critical&style=social)  | KDD 2024

| Multivariable |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |    UniTime | [UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3589334.3645434) | [Pytorch](https://github.com/liuxu77/UniTime)  
![Stars](https://img.shields.io/github/stars/liuxu77/UniTime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liuxu77/UniTime?color=critical&style=social)  | WWW 2024

| Multivariable | Ross 
 Saratoga 
  UpperPen  
 SFC  |    DAN | [Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/27768) | [Pytorch](https://github.com/davidanastasiu/dan)  
![Stars](https://img.shields.io/github/stars/davidanastasiu/dan?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/davidanastasiu/dan?color=critical&style=social)  | AAAI 2024

| Multivariable | ILI 
 Weather 
  Traffic  
 Electricity 
  ETT 
 Exchange  |    HDMixer | [HDMixer: Hierarchical Dependency with Extendable Patch for Multivariate Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/29155) | [Pytorch](https://github.com/hqh0728/HDMixer)  
![Stars](https://img.shields.io/github/stars/hqh0728/HDMixer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hqh0728/HDMixer?color=critical&style=social)  | AAAI 2024

| Multivariable |  PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  
  England 
  TaxiBJ 
  PEMS-BAY  |  STPGNN  | [Spatio-Temporal Pivotal Graph Neural Networks for Traffic Flow Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/28707) | None  | AAAI 2024

| Multivariable | FD001 
 FD002 
  FD003  
 FD004  |    FC-STGNN | [Fully-Connected Spatial-Temporal Graph for Multivariate Time-Series Data](https://ojs.aaai.org/index.php/AAAI/article/view/29500) | [Pytorch](https://github.com/Frank-Wang-oss/FCSTGNN)  
![Stars](https://img.shields.io/github/stars/Frank-Wang-oss/FCSTGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Frank-Wang-oss/FCSTGNN?color=critical&style=social)  | AAAI 2024

| Multivariable | PEMS04  
 PEMS08 
 blockchain  |   TMP-Nets  | [Time-Aware Knowledge Representations of Dynamic Objects with Multidimensional Persistence](https://ojs.aaai.org/index.php/AAAI/article/view/29051) | None  | AAAI 2024

| Multivariable | METR-LA 
 PEMS-BAY   |  ModWaveMLP | [ModWaveMLP: MLP-Based Mode Decomposition and Wavelet Denoising Model to Defeat Complex Structures in Traffic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/28753) | [TF](https://github.com/Kqingzheng/ModWaveMLP)  
![Stars](https://img.shields.io/github/stars/Kqingzheng/ModWaveMLP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Kqingzheng/ModWaveMLP?color=critical&style=social)  | AAAI 2024

| Multivariable |Flight    
 Weather  
 ETT 
  Electricity  
 Exchange   |  MSGNet | [MSGNet: Learning Multi-Scale Inter-series Correlations for Multivariate Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/28991) | [Pytorch](https://github.com/YoZhibo/MSGNet)  
![Stars](https://img.shields.io/github/stars/YoZhibo/MSGNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YoZhibo/MSGNet?color=critical&style=social)  | AAAI 2024

| Multivariable |  Self-PeMS  |  DLF | [Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective](https://ojs.aaai.org/index.php/AAAI/article/view/28759) | [Pytorch](https://github.com/wangbinwu13116175205/DLF)  
![Stars](https://img.shields.io/github/stars/wangbinwu13116175205/DLF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wangbinwu13116175205/DLF?color=critical&style=social)  | AAAI 2024

| Multivariable |ETT    
 Weather  
 ILI  
 Exchange   |   HTV-Trans | [Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/29483) | [Pytorch](https://github.com/flare200020/HTV_Trans)  
![Stars](https://img.shields.io/github/stars/flare200020/HTV_Trans?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/flare200020/HTV_Trans?color=critical&style=social)  | AAAI 2024

| Multivariable |A-share   
 Cross-Market  
 ETT   |  ST-DAN| [Adaptive Meta-Learning Probabilistic Inference Framework for Long Sequence Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/29661) | [Pytorch](https://github.com/Zhu-JP/AMPIF)  
![Stars](https://img.shields.io/github/stars/Zhu-JP/AMPIF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Zhu-JP/AMPIF?color=critical&style=social)  | AAAI 2024

| Six  |  [TimesNet_data](https://github.com/thuml/Time-Series-Library)   |  CTRL | [An NCDE-based Framework for Universal Representation Learning of Time Series](https://www.ijcai.org/proceedings/2024/511) | [Pytorch](https://github.com/LiuZH-19/CTRL)  
![Stars](https://img.shields.io/github/stars/LiuZH-19/CTRL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LiuZH-19/CTRL?color=critical&style=social)  | IJCAI 2024

| Traffic  | PEMS3478   |  STD-MAE | [Spatial-Temporal-Decoupled Masked Pre-training for Spatiotemporal Forecasting](https://www.ijcai.org/proceedings/2024/442) | [Pytorch](https://github.com/Jimmy-7664/STD-MAE)  
![Stars](https://img.shields.io/github/stars/Jimmy-7664/STD-MAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Jimmy-7664/STD-MAE?color=critical&style=social)  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | DERITS | [Deep Frequency Derivative Learning for Non-stationary Time Series Forecasting](https://www.ijcai.org/proceedings/2024/436) | None   | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | Skip-Timeformer | [Skip-Timeformer: Skip-Time Interaction Transformer for Long Sequence Time-Series Forecasting](https://www.ijcai.org/proceedings/2024/608) | None  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | VCformer | [VCformer: Variable Correlation Transformer with Inherent Lagged Correlation for Multivariate Time Series Forecasting](https://www.ijcai.org/proceedings/2024/590) | [Pytorch](https://github.com/CSyyn/VCformer)  
![Stars](https://img.shields.io/github/stars/CSyyn/VCformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CSyyn/VCformer?color=critical&style=social)  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | LeRet | [LeRet: Language-Empowered Retentive Network for Time Series Forecasting](https://www.ijcai.org/proceedings/2024/460) | [Pytorch](https://github.com/hqh0728/LeRet)  
![Stars](https://img.shields.io/github/stars/hqh0728/LeRet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hqh0728/LeRet?color=critical&style=social)  | IJCAI 2024

| Missing Variate   |    METR-LA 
 Solar 
 Traffic 
 ECG5000  | SDformer | [SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting](https://www.ijcai.org/proceedings/2024/228) | None  | IJCAI 2024

| Traffic   |    METR-LA 
 PEMS-BAY 
 PEMSD7M  | DCST | [Make Graph Neural Networks Great Again: A Generic Integration Paradigm of Topology-Free Patterns for Traffic Speed Prediction](https://www.ijcai.org/proceedings/2024/288) | [Pytorch](https://github.com/ibizatomorrow/DCST)  
![Stars](https://img.shields.io/github/stars/ibizatomorrow/DCST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ibizatomorrow/DCST?color=critical&style=social)  | IJCAI 2024

| Traffic   |    METR-LA 
 PEMS-BAY   | ST-nFBST | [Full Bayesian Significance Testing for Neural Networks in Traffic Forecasting](https://www.ijcai.org/proceedings/2024/245) | [Pytorch](https://github.com/liuzh-buaa/ST-nFBST)  
![Stars](https://img.shields.io/github/stars/liuzh-buaa/ST-nFBST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liuzh-buaa/ST-nFBST?color=critical&style=social)  | IJCAI 2024

| multi-source  
  SSL |  BikeIn 
 BikeOut 
 TaxiIn 
 TaxiOut 
 Air  | MoSSL | [Multi-Modality Spatio-Temporal Forecasting via Self-Supervised Learning](https://www.ijcai.org/proceedings/2024/223) | [Pytorch](https://github.com/beginner-sketch/MoSSL)  
![Stars](https://img.shields.io/github/stars/beginner-sketch/MoSSL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/beginner-sketch/MoSSL?color=critical&style=social)  | IJCAI 2024

| Traffic 
 CrossCity  |    METR-LA 
 PEMS-BAY 
 DiDiCD 
 DiDiSZ  | pFedCTP  | [Personalized Federated Learning for Cross-City Traffic Prediction](https://www.ijcai.org/proceedings/2024/611) | [Pytorch](https://github.com/ZYuSdu/pFedCTP)  
![Stars](https://img.shields.io/github/stars/ZYuSdu/pFedCTP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ZYuSdu/pFedCTP?color=critical&style=social)  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | SDformer | [SDformer: Transformer with Spectral Filter and Dynamic Attention for Multivariate Time Series Long-term Forecasting](https://www.ijcai.org/proceedings/2024/629) | [Pytorch](https://github.com/zhouziyu02/SDformer)  
![Stars](https://img.shields.io/github/stars/zhouziyu02/SDformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhouziyu02/SDformer?color=critical&style=social)  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | SpecAR-Net | [SpecAR-Net: Spectrogram Analysis and Representation Network for Time Series](https://www.ijcai.org/proceedings/2024/433) | [Pytorch](https://github.com/Dongyi2go/SpecAR_Net)  
![Stars](https://img.shields.io/github/stars/Dongyi2go/SpecAR_Net?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Dongyi2go/SpecAR_Net?color=critical&style=social)  | IJCAI 2024

| Multivariable   |    [TimesNet_data](https://github.com/thuml/Time-Series-Library)   | SCAT | [SCAT: A Time Series Forecasting with Spectral Central Alternating Transformers](https://www.ijcai.org/proceedings/2024/622) | None | IJCAI 2024

| Traffic  | Traffic 
 ECG 
  COVID-19 
 Wiki 
 Solar   | DIAN | [Decoupled Invariant Attention Network for Multivariate Time-series Forecasting](https://www.ijcai.org/proceedings/2024/275) | [Pytorch](https://github.com/xhh39/DIAN)  
![Stars](https://img.shields.io/github/stars/xhh39/DIAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/xhh39/DIAN?color=critical&style=social)  | IJCAI 2024

| Traffic  | Wave 
 Wind 
  Air   | EPL | [Self-adaptive Extreme Penalized Loss for Imbalanced Time Series Prediction](https://www.ijcai.org/proceedings/2024/568) | [Pytorch](https://github.com/Ldiper/EPL)  
![Stars](https://img.shields.io/github/stars/Ldiper/EPL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Ldiper/EPL?color=critical&style=social)  | IJCAI 2024

| Multivariable | ETT 
 Electricity 
  Traffic  
 Weather   
 Exchange  |    U-Mixer | [U-Mixer: An Unet-Mixer Architecture with Stationarity Correction for Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/29337) | None | AAAI 2024

| Irregular  |USHCN    
 MIMIC-III  
 MIMIC-IV  
 Physionet-12   |  GraFITi | [GraFITi: Graphs for Forecasting Irregularly Sampled Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/29560) | [Pytorch](https://github.com/yalavarthivk/GraFITi)  
![Stars](https://img.shields.io/github/stars/yalavarthivk/GraFITi?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yalavarthivk/GraFITi?color=critical&style=social)  | AAAI 2024

| Traffic 
 Flow |  PEMS03 
 PEMS04 
 PEMS07 
 PEMS08  | MultiSPANS  | [MultiSPANS: A Multi-range Spatial-Temporal Transformer Network for Traffic Forecast via Structural Entropy Optimization](https://dl.acm.org/doi/10.1145/3616855.3635820) |  [Pytorch](https://github.com/SELGroup/MultiSPANS)  
![Stars](https://img.shields.io/github/stars/SELGroup/MultiSPANS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SELGroup/MultiSPANS?color=critical&style=social)   | WSDM 2024

| Multivariable | SIP  
 NYC   
 METR-LA  | CreST  | [CreST: A Credible Spatiotemporal Learning Framework for Uncertainty-aware Traffic Forecasting](https://dl.acm.org/doi/10.1145/3616855.3635759) | None  | WSDM 2024

| Multivariable | Web Traffic  
 Labour   
 Traffic 
  Tourism   | HTS  | [NeuralReconciler for Hierarchical Time Series Forecasting](https://dl.acm.org/doi/10.1145/3616855.3635806) | None  | WSDM 2024

| Multivariable | NYC13    
 BikeNYC   
 Chicago21  
  Chicago22   | CityCAN  | [CityCAN: Causal Attention Network for Citywide Spatio-Temporal Forecasting](https://dl.acm.org/doi/10.1145/3616855.3635764) | None  | WSDM 2024

| Multivariable |  Solar 
 Wiki 
  Traffic 
 ECG 
 Electricity  
  COVID-19   
 Weather  
  ETT |    FreTS | [Frequency-domain MLPs are More Effective Learners in Time Series Forecasting](https://proceedings.neurips.cc/paper_files/paper/2023/hash/f1d16af76939f476b5f040fd1398c0a3-Abstract-Conference.html) | [Pytorch](https://github.com/aikunyi/FreTS)  
![Stars](https://img.shields.io/github/stars/aikunyi/FreTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/aikunyi/FreTS?color=critical&style=social)  | NIPS 2023

| LLM4TS 
 Zero Shot |  Darts  
 Monash  
  Informer   |    - | [Large Language Models Are Zero-Shot Time Series Forecasters](https://proceedings.neurips.cc/paper_files/paper/2023/hash/3eb7ca52e8207697361b2c0fb3926511-Abstract-Conference.html) | [LLM](https://github.com/ngruver/llmtime)  
![Stars](https://img.shields.io/github/stars/ngruver/llmtime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ngruver/llmtime?color=critical&style=social)  | NIPS 2023

| Zero Shot |  ECL  
ETT  
 Exchange 
 ILI 
 Traffic   
   Weather    |    ForecastPFN | [ForecastPFN: Synthetically-Trained Zero-Shot Forecasting](https://proceedings.neurips.cc/paper_files/paper/2023/hash/0731f0e65559059eb9cd9d6f44ce2dd8-Abstract-Conference.html) | [TF](https://github.com/abacusai/forecastpfn)  
![Stars](https://img.shields.io/github/stars/abacusai/forecastpfn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/abacusai/forecastpfn?color=critical&style=social)  | NIPS 2023

| Multivariable |  ECL   
  Traffic  
ETT 
   Weather    |    WITRAN | [WITRAN: Water-wave Information Transmission and Recurrent Acceleration Network for Long-range Time Series Forecasting](https://proceedings.neurips.cc/paper_files/paper/2023/hash/2938ad0434a6506b125d8adaff084a4a-Abstract-Conference.html) | [Pytorch](https://github.com/Water2sea/WITRAN)  
![Stars](https://img.shields.io/github/stars/Water2sea/WITRAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Water2sea/WITRAN?color=critical&style=social)  | NIPS 2023

| Multivariable |  ETT  
  Weather   
  PEMS03 
 PEMS04 
  PEMS07  
 PEMS08    |    Neural Lad | [Neural Lad: A Neural Latent Dynamics Framework for Times Series Modeling](https://openreview.net/forum?id=bISkJSa5Td) | None | NIPS 2023

| Multivariable |  ETT  
 Weather  
  Electricity   |    OneNet | [OneNet: Enhancing Time Series Forecasting Models under Concept Drift by Online Ensembling](https://proceedings.neurips.cc/paper_files/paper/2023/hash/dd6a47bc0aad6f34aa5e77706d90cdc4-Abstract-Conference.html) | [Pytorch](https://github.com/yfzhang114/OneNet)  
![Stars](https://img.shields.io/github/stars/yfzhang114/OneNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yfzhang114/OneNet?color=critical&style=social)  | NIPS 2023

| Multivariable 
 Solar Irradiance|  CAB 
 TAM  |    CrossViVit | [Improving day-ahead Solar Irradiance Time Series Forecasting by Leveraging Spatio-Temporal Context](https://openreview.net/forum?id=x5ZruOa4ax) | [Pytorch](https://github.com/gitbooo/CrossViVit)  
![Stars](https://img.shields.io/github/stars/gitbooo/CrossViVit?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gitbooo/CrossViVit?color=critical&style=social)  | NIPS 2023

| Multivariable |  ECL  
ETT 
 Exchange 
  ILI 
  Traffic  
  Weather    |    Koopa | [Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors](https://proceedings.neurips.cc/paper_files/paper/2023/hash/dd6a47bc0aad6f34aa5e77706d90cdc4-Abstract-Conference.html) | [Pytorch](https://github.com/thuml/Koopa)  
![Stars](https://img.shields.io/github/stars/thuml/Koopa?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/Koopa?color=critical&style=social)  | NIPS 2023

| Multivariable | GPVAR 
 METR-LA 
 PEMS-BAY 
 PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  
 CER-E
AQI     |    TTS-IMP | [Taming Local Effects in Graph-based Spatiotemporal Forecasting](https://openreview.net/forum?id=x2PH6q32LR) | [Pytorch](https://github.com/Graph-Machine-Learning-Group/taming-local-effects-stgnns)  
![Stars](https://img.shields.io/github/stars/Graph-Machine-Learning-Group/taming-local-effects-stgnns?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Graph-Machine-Learning-Group/taming-local-effects-stgnns?color=critical&style=social)  | NIPS 2023

| Multivariable |  PEMS08 
 AIR-BJ 
  AIR-GZ     |    CaST | [Deciphering Spatio-Temporal Graph Forecasting: A Causal Lens and Treatment](https://openreview.net/forum?id=17Zkztjlgt) | [Pytorch](https://github.com/yutong-xia/CaST)  
![Stars](https://img.shields.io/github/stars/yutong-xia/CaST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yutong-xia/CaST?color=critical&style=social)  | NIPS 2023

| Multivariable |  PEMS08 
 METR-LA 
  NYC Taxi 
 NYC Bike     |    GPT-ST | [GPT-ST: Generative Pre-Training of Spatio-Temporal Graph Neural Networks](https://openreview.net/forum?id=nMH5cUaSj8) | [Pytorch](https://github.com/HKUDS/GPT-ST)  
![Stars](https://img.shields.io/github/stars/HKUDS/GPT-ST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HKUDS/GPT-ST?color=critical&style=social)  | NIPS 2023

| Multivariable |  Solar  
 Wiki 
 Traffic 
 COVID-19     |    FourierGNN | [FourierGNN: Rethinking Multivariate Time Series Forecasting from a Pure Graph Perspective](https://proceedings.neurips.cc/paper_files/paper/2023/hash/dc1e32dd3eb381dbc71482f6a96cbf86-Abstract-Conference.html) | [Pytorch](https://github.com/aikunyi/FourierGNN)  
![Stars](https://img.shields.io/github/stars/aikunyi/FourierGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/aikunyi/FourierGNN?color=critical&style=social)  | NIPS 2023

| Multivariable | ETT  
   Weather  
 Electricity  
 Traffic    |    SimMTM | [SimMTM: A Simple Pre-Training Framework for Masked Time-Series Modeling](https://proceedings.neurips.cc/paper_files/paper/2023/hash/5f9bfdfe3685e4ccdbc0e7fb29cccf2a-Abstract-Conference.html) | [Pytorch](https://github.com/thuml/SimMTM)  
![Stars](https://img.shields.io/github/stars/thuml/SimMTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/SimMTM?color=critical&style=social)  | NIPS 2023

| Multivariable | ETT 
 Electricity  
  Exchange  
  Traffic  
  Weather   
  ILI   |    BasisFormer | [BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable Basis](https://proceedings.neurips.cc/paper_files/paper/2023/hash/e150e6d0a1e5214740c39c6e4503ba7a-Abstract-Conference.html) | [Pytorch](https://github.com/nzl5116190/Basisformer)  
![Stars](https://img.shields.io/github/stars/nzl5116190/Basisformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nzl5116190/Basisformer?color=critical&style=social)  | NIPS 2023

| Irregular |  Neonate  
 Traffic  
  MIMIC 
  StackOverflow 
 BookOrder 
 Exchange 
 ETT 
 ILI
  Weather|    ContiFormer | [ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling](https://proceedings.neurips.cc/paper_files/paper/2023/hash/9328208f88ec69420031647e6ff97727-Abstract-Conference.html) | [Pytorch](https://github.com/microsoft/SeqML/tree/main/ContiFormer)   | NIPS 2023

| Multivariable |  Electricity 
 Exchange 
 Traffic 
  Weather  
  ILI  
 ETT  |    SAN | [Adaptive Normalization for Non-stationary Time Series Forecasting: A Temporal Slice Perspective](https://proceedings.neurips.cc/paper_files/paper/2023/hash/2e19dab94882bc95ed094c4399cfda02-Abstract-Conference.html) | [Pytorch](https://github.com/icantnamemyself/SAN)  
![Stars](https://img.shields.io/github/stars/icantnamemyself/SAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/icantnamemyself/SAN?color=critical&style=social)  | NIPS 2023

| Multivariable |  ETT  
 Electricity 
 Exchange 
 Traffic  
  Weather  
  ILI   |    DeepTime (Framework, 
 Fourier Features, 
 Meta-optimization)| [ Learning Deep Time-index Models for Time Series Forecasting](https://openreview.net/forum?id=pgcfCCNQXO) | [Pytorch](https://github.com/salesforce/DeepTime)  
![Stars](https://img.shields.io/github/stars/salesforce/DeepTime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/salesforce/DeepTime?color=critical&style=social)  | ICML 2023

| Multivariable |  Crime 
 CHI-Taxi  
 NYC-Bike 
 NYC-Taxi
 CHI-House
 NYC-House    |  GraphST | [Spatial-Temporal Graph Learning with Adversarial Contrastive Adaptation](https://openreview.net/forum?id=LVARH5wXM9) | [Pytorch](https://github.com/HKUDS/GraphST)  
![Stars](https://img.shields.io/github/stars/HKUDS/GraphST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HKUDS/GraphST?color=critical&style=social)  | ICML 2023

| Multivariable |  Synthetic 
 Taxi  
 Electricity 
 Traffic    |    FeatureP (Feature Enhancement) | [Feature Programming for Multivariate Time Series Prediction](https://openreview.net/forum?id=LVARH5wXM9) | [Pytorch](https://github.com/SirAlex900/FeatureProgramming)  
![Stars](https://img.shields.io/github/stars/SirAlex900/FeatureProgramming?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SirAlex900/FeatureProgramming?color=critical&style=social)  | ICML 2023

| Multivariable |  NorPool  
 Caiso  
 Weather  
  ETT   
 Wind 
 Traffic  
 Electricity  
 Exchange |    TimeDiff    | [Non-autoregressive Conditional Diffusion Models for Time Series Prediction](https://openreview.net/forum?id=wZsnZkviro) | None| ICML 2023

| Multivariable | ETT 
 Electricity 
 Exchange 
 Traffic  
 Weather  
  ILI  |    MICN    | [MICN: Multi-scale Local and Global Context Modeling for Long-term Series Forecasting](https://openreview.net/forum?id=zt53IDUR1U) | [Pytorch](https://github.com/wanghq21/MICN)  
![Stars](https://img.shields.io/github/stars/wanghq21/MICN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wanghq21/MICN?color=critical&style=social) | ICLR 2023

| Multivariable | ETT 
 Weather 
 Electricity 
  ILI  
 Traffic    |    Crossformer    | [Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting](https://openreview.net/forum?id=vSVLM2j9eie) | [Pytorch](https://github.com/Thinklab-SJTU/Crossformer)  
![Stars](https://img.shields.io/github/stars/Thinklab-SJTU/Crossformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Thinklab-SJTU/Crossformer?color=critical&style=social)  | ICLR 2023

| Forecast 
 Imputation 
 Classifi  
 AnomalyDet | ETT 
 M4 
 Electricity 
  Weather  
SMD,MSL 
 SMAP,SWaT 
 PSM  |    TimesNet    | [TimesNet: Temporal 2D-Variation Modeling for General Time Series Analysis](https://openreview.net/forum?id=ju_Uqw384Oq) | [Pytorch](https://github.com/thuml/Time-Series-Library) 
![Stars](https://img.shields.io/github/stars/thuml/Time-Series-Library?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/Time-Series-Library?color=critical&style=social) | ICLR 2023

| Multivariable |  |    Meta-SSM    | [Sequential Latent Variable Models for Few-Shot High-Dimensional Time-Series Forecasting](https://openreview.net/forum?id=7C9aRX2nBf2) | [Pytorch](https://github.com/john-x-jiang/meta_ssm) 
![Stars](https://img.shields.io/github/stars/john-x-jiang/meta_ssm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/john-x-jiang/meta_ssm?color=critical&style=social) | ICLR 2023

| Multivariable |  ETT 
 Electricity  
 Traffic  
 Weather  |   FSNet   | [Learning Fast and Slow for Time Series Forecasting](https://openreview.net/forum?id=q-PbpHD3EOk) | [Pytorch](https://github.com/salesforce/fsnet) 
![Stars](https://img.shields.io/github/stars/salesforce/fsnet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/salesforce/fsnet?color=critical&style=social) | ICLR 2023

| Robust 
 Multivariable |  Traffic 
 Taxi  
 Wiki  
 Electricity  |        | [Robust Multivariate Time-Series Forecasting: Adversarial Attacks and Defense Mechanisms](https://openreview.net/forum?id=ctmLBs8lITa) | [Amazon](https://github.com/awslabs/gluonts/tree/dev/src/gluonts/nursery) | ICLR 2023

| Multivariable |  Electricity 
 Crypto  
 M4  
 Traffic 
 Exchange |   KNF     | [Koopman Neural Operator Forecaster for Time-series with Temporal Distributional Shifts](https://openreview.net/forum?id=kUmdmHxK5N) | [Pytorch](https://github.com/google-research/google-research/tree/master/KNF) 
![Stars](https://img.shields.io/github/stars/google-research/google-research/tree/master/KNF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/google-research/google-research/tree/master/KNF?color=critical&style=social) | ICLR 2023

| Multivariable |  ETT 
 Weather  
 Electricity  
 Traffic 
 Exchange |   SpaceTime     | [Effectively Modeling Time Series with Simple Discrete State Spaces](https://openreview.net/forum?id=2EpjkjzdCAa) | [Pytorch](https://github.com/HazyResearch/spacetime) 
![Stars](https://img.shields.io/github/stars/HazyResearch/spacetime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HazyResearch/spacetime?color=critical&style=social) | ICLR 2023

| Multivariable |  Weather 
 Traffic  
 Electricity  
 ILI 
 ETT |   PatchTST     | [A Time Series is Worth 64 Words: Long-term Forecasting with Transformers](https://openreview.net/forum?id=Jbdc0vTOcol) | [Pytorch](https://github.com/yuqinie98/PatchTST) 
![Stars](https://img.shields.io/github/stars/yuqinie98/PatchTST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yuqinie98/PatchTST?color=critical&style=social) | ICLR 2023

| Multivariable |  Exchange  
  Weather 
   Electricity 
 Traffic  
 ILI  |   Scaleformer     | [Scaleformer: Iterative Multi-scale Refining Transformers for Time Series Forecasting](https://openreview.net/forum?id=sCrnllCtjoE) | [Pytorch](https://github.com/BorealisAI/scaleformer) 
![Stars](https://img.shields.io/github/stars/BorealisAI/scaleformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BorealisAI/scaleformer?color=critical&style=social) | ICLR 2023

| Multivariable 
 classification 
 AnomalyDec |  Electricity  
 Weather 
 ETTm1 
 MSL 
  SMD 
  SMAP   |    SBT    | [Sparse Binary Transformers for Multivariate Time Series Modeling](https://dl.acm.org/doi/abs/10.1145/3580305.3599508) |   [Pytorch](https://github.com/mattgorb/sparse-binary-transformers) 
![Stars](https://img.shields.io/github/stars/mattgorb/sparse-binary-transformers?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mattgorb/sparse-binary-transformers?color=critical&style=social)   | KDD 2023

| Multivariable |  SIP  
 METR-LA 
 KnowAir 
 Electricity |    CauSTG    | [Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning](https://dl.acm.org/doi/10.1145/3580305.3599529) |  [Pytorch](https://github.com/zzyy0929/KDD23-CauSTG) 
![Stars](https://img.shields.io/github/stars/zzyy0929/KDD23-CauSTG?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zzyy0929/KDD23-CauSTG?color=critical&style=social)   | KDD 2023

| Robust 
 Multivariable |  PEMS-BAY  
  PEMS04  |    RDAT    | [Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training](https://dl.acm.org/doi/10.1145/3580305.3599492) |  [Pytorch](https://github.com/usail-hkust/RDAT) 
![Stars](https://img.shields.io/github/stars/usail-hkust/RDAT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/usail-hkust/RDAT?color=critical&style=social)   | KDD 2023

| Multivariable | Beijing 
  Chengdu  
 Harbin  |    Frigate    | [Frigate: Frugal Spatio-temporal Forecasting on Road Networks](https://dl.acm.org/doi/10.1145/3580305.3599357) |  [Pytorch](https://github.com/idea-iitd/frigate) 
![Stars](https://img.shields.io/github/stars/idea-iitd/frigate?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/idea-iitd/frigate?color=critical&style=social)   | KDD 2023

|Multivariable | XC-Traffic  
  NYC-Traffic  |    GCIM    | [Generative Causal Interpretation Model for Spatio-Temporal Representation Learning](https://doi.org/10.1145/3580305.3599363) | None | KDD 2023

| Multivariable |  Tourism  
 Labour 
 Wiki 
 Flu-Symptoms 
 FB-Survey |    PROFHiT    | [When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting](https://dl.acm.org/doi/10.1145/3580305.3599529) |  [Pytorch](https://github.com/AdityaLab/Profhit) 
![Stars](https://img.shields.io/github/stars/AdityaLab/Profhit?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AdityaLab/Profhit?color=critical&style=social)   | KDD 2023

| Multivariable 
 Under Miss |  AQI-36  
 AQI 
 PEMS-BAY 
 CER-E 
  Healthcare 
  SMAP   |    MIDM    | [An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series](https://doi.org/10.1145/3580305.3599257) |    [Author](http://home.ustc.edu.cn/~wx309/)   | KDD 2023

| Multivariable |   PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  
 etc.|    Localised    | [Localised Adaptive Spatial-Temporal Graph Neural Network](https://dl.acm.org/doi/10.1145/3580305.3599418) | None  | KDD 2023

| Multivariable |  PEMS3-Stream   |    PECPM    | [Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction](https://doi.org/10.1145/3580305.3599463) | None  | KDD 2023

| Multivariable |  Tourism  
 Wiki 
 Traffic |    HPO    | [Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting](https://dl.acm.org/doi/10.1145/3580305.3599529) |   None | KDD 2023   

| Multivariable |  Weather  
 Traffic  
 Electricity 
  ETT   |    TSMixer    | [TSMixer: Lightweight MLP-Mixer Model for Multivariate Time Series Forecasting](https://doi.org/10.1145/3580305.3599533) | None| KDD 2023

| Transfer 
 Traffic 
 Forecasting |  PEMSD7M  
 PEMSD7M 
 METR-LA 
 PEMS-BAY  |    TransGTR    | [Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities](https://dl.acm.org/doi/10.1145/3580305.3599529) |   [Author](https://github.com/KL4805)    | KDD 2023

| Multivariable | ETT 
 Traffic  
 Electricity   
 Exchange   
 Weather  
   ILI  |  DLinear     | [Are Transformers Effective for Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/26317) | [Pytorch](https://github.com/cure-lab/LTSF-Linear) 
![Stars](https://img.shields.io/github/stars/cure-lab/LTSF-Linear?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/cure-lab/LTSF-Linear?color=critical&style=social) | AAAI 2023  

| Multivariable | METR-LA  
 PEMSD7M  |  STC-Dropout    | [Easy Begun Is Half Done: Spatial-Temporal Graph Modeling with ST-Curriculum Dropout](https://ojs.aaai.org/index.php/AAAI/article/view/25590) | [Pytorch](https://github.com/Urban-Computing/STC-Dropout) 
![Stars](https://img.shields.io/github/stars/Urban-Computing/STC-Dropout?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Urban-Computing/STC-Dropout?color=critical&style=social) | AAAI 2023  

| Multivariable | BJ-Bike 
 NYC-Bike  |  STNSCM    | [Spatio-Temporal Neural Structural Causal Models for Bike Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/25542) | [Pytorch](https://github.com/EternityZY/STNSCM) 
![Stars](https://img.shields.io/github/stars/EternityZY/STNSCM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/EternityZY/STNSCM?color=critical&style=social) | AAAI 2023  

| Multivariable | XC-Trans 
 XC-Speed  | CCHMM   | [Causal Conditional Hidden Markov Model for Multimodal Traffic Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/25619) | [Pytorch](https://github.com/EternityZY/CCHMM) 
![Stars](https://img.shields.io/github/stars/EternityZY/CCHMM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/EternityZY/CCHMM?color=critical&style=social) | AAAI 2023  

| Multivariable | NYCBike1 
 NYCBike2 
  NYCTaxi 
  BJTaxi |  ST-SSL    | [Spatio-Temporal Self-Supervised Learning for Traffic Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/25555) | [Pytorch](https://github.com/Echo-Ji/ST-SSL) 
![Stars](https://img.shields.io/github/stars/Echo-Ji/ST-SSL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Echo-Ji/ST-SSL?color=critical&style=social) | AAAI 2023  

| Multivariable | PV-US  
 CER-En  |  SGP     | [Scalable Spatiotemporal Graph Neural Networks](https://ojs.aaai.org/index.php/AAAI/article/view/25880) | [Pytorch](https://github.com/Graph-Machine-Learning-Group/sgp) 
![Stars](https://img.shields.io/github/stars/Graph-Machine-Learning-Group/sgp?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Graph-Machine-Learning-Group/sgp?color=critical&style=social) | AAAI 2023  

| Multivariable | Electricity 
 Solar  
  PEMS-BAY  
 METR-LA |  SRD     | [Learning Decomposed Spatial Relations for Multi-Variate Time-Series Modeling](https://ojs.aaai.org/index.php/AAAI/article/view/25915) | [Pytorch](https://github.com/Arthur-Null/SRD) 
![Stars](https://img.shields.io/github/stars/Arthur-Null/SRD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Arthur-Null/SRD?color=critical&style=social) | AAAI 2023  

| Multivariable | ETT  
 Electricity  |  InfoTS     | [Time Series Contrastive Learning with Information-Aware Augmentations](https://ojs.aaai.org/index.php/AAAI/article/view/25575) | [Pytorch](https://github.com/chengw07/InfoTS) 
![Stars](https://img.shields.io/github/stars/chengw07/InfoTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chengw07/InfoTS?color=critical&style=social) | AAAI 2023  

| Multivariable |   PhysioNet  
   MIMIC-III    
  Activity  
  Appliances Energy |  PrimeNet   | [PrimeNet: Pre-training for Irregular Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/25876) | [Pytorch](https://github.com/ranakroychowdhury/PrimeNet) 
![Stars](https://img.shields.io/github/stars/ranakroychowdhury/PrimeNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ranakroychowdhury/PrimeNet?color=critical&style=social) | AAAI 2023  

| Multivariable |   Electricity  
  ETT    
 Weather  |   Dish-TS    | [Dish-TS: A General Paradigm for Alleviating Distribution Shift in Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/25914) | [Pytorch](https://github.com/weifantt/Dish-TS) 
![Stars](https://img.shields.io/github/stars/weifantt/Dish-TS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/weifantt/Dish-TS?color=critical&style=social) | AAAI 2023  

| Multivariable |  ETT 
 Electricity   
 Exchange  
 Traffic    
 Weather  
   ILI  |  NHITS   | [NHITS: Neural Hierarchical Interpolation for Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/25854) | [Pytorch](https://github.com/Nixtla/neuralforecast) 
![Stars](https://img.shields.io/github/stars/Nixtla/neuralforecast?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Nixtla/neuralforecast?color=critical&style=social) | AAAI 2023  

| Multivariable |   METR-LA  
   ETT    
 Weather   |  MegaCRN   | [Spatio-Temporal Meta-Graph Learning for Traffic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/25976) | [Pytorch](https://github.com/deepkashiwa20/MegaCRN) 
![Stars](https://img.shields.io/github/stars/deepkashiwa20/MegaCRN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/deepkashiwa20/MegaCRN?color=critical&style=social) | AAAI 2023  

| Multivariable | Santa 
 Traffic  |   NEC+     | [An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks](https://ojs.aaai.org/index.php/AAAI/article/view/26276) | [Pytorch](https://github.com/davidanastasiu/NECPlus) 
![Stars](https://img.shields.io/github/stars/davidanastasiu/NECPlus?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/davidanastasiu/NECPlus?color=critical&style=social) | AAAI 2023  

| Extreme MTSF | Electricity  
 Solar  
 Weather 
 Traffic  |   WaveForM     | [WaveForM: Graph Enhanced Wavelet Learning for Long Sequence Forecasting of Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/26276) | [Pytorch](https://github.com/alanyoungCN/WaveForM) 
![Stars](https://img.shields.io/github/stars/alanyoungCN/WaveForM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/alanyoungCN/WaveForM?color=critical&style=social) | AAAI 2023  

| Multivariable | PEMS04 
  PEMS07  
 PEMS08    
  NYCTaxi   
  CHBike  
  TDrive |   PDFormer     | [PDFormer: Propagation Delay-Aware Dynamic Long-Range Transformer for Traffic Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/25556) | [Pytorch](https://github.com/BUAABIGSCity/PDFormer) 
![Stars](https://img.shields.io/github/stars/BUAABIGSCity/PDFormer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BUAABIGSCity/PDFormer?color=critical&style=social) | AAAI 2023  

| Multivariable |  AmapBeijing 
 AmapChengdu   |   STGNPP     | [Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/26669) | None | AAAI 2023

| Multivariable |  ETT 
 Electricity  
 Exchange   
 Traffic 
 Weather 
  ILI |   InParformer     | [InParformer: Evolutionary Decomposition Transformers with Interactive Parallel Attention for Long-Term Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/25845) | None | AAAI 2023

| Multivariable |   Tourism  
  Labour   
   M5   |  SLOTH   | [SLOTH: Structured Learning and Task-Based Optimization for Time Series Forecasting on Hierarchies](https://ojs.aaai.org/index.php/AAAI/article/view/26350) | None | AAAI 2023  

| Multivariable |   Wind 
  Solar    |  eForecaster   | [eForecaster: Unifying Electricity Forecasting with Robust, Flexible, and Explainable Machine Learning Algorithms](https://ojs.aaai.org/index.php/AAAI/article/view/26853) | None | AAAI 2023  

| Multivariable | NYCTaxi 
 PEMS04 |  AutoSTL    | [AutoSTL: Automated Spatio-Temporal Multi-Task Learning](https://ojs.aaai.org/index.php/AAAI/article/view/25616) | None | AAAI 2023  

| Multivariable | METR-LA 
 PEMS-BAY |    Trafformer    | [Trafformer: Unify Time and Space in Traffic Prediction](https://doi.org/10.1609/aaai.v37i7.25980) | None| AAAI 2023

| Multivariable | Electricity 
  PM2.5  
 Exchange   |   DeLELSTM     | [DeLELSTM: Decomposition-based Linear Explainable LSTM to Capture Instantaneous and Long-term Effects in Time Series](https://www.ijcai.org/proceedings/2023/478) | [Pytorch](https://github.com/wangcq01/DeLELSTM) 
![Stars](https://img.shields.io/github/stars/wangcq01/DeLELSTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wangcq01/DeLELSTM?color=critical&style=social) | IJCAI 2023  

| Multivariable | NYC-Bike 
 PEMS-BAY   
  PEMS08 |   ReMo     | [Not Only Pairwise Relationships: Fine-Grained Relational Modeling for Multivariate Time Series Forecasting](https://www.ijcai.org/proceedings/2023/491) | [Pytorch](https://github.com/beginner-sketch/gmrl) 
![Stars](https://img.shields.io/github/stars/beginner-sketch/gmrl?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/beginner-sketch/gmrl?color=critical&style=social) | IJCAI 2023  

| Multivariable | NASA |   MetePFL     | [Prompt Federated Learning for Weather Forecasting: Toward Foundation Models on Meteorological Data](https://www.ijcai.org/proceedings/2023/393) | [Pytorch](https://github.com/shengchaochen82/MetePFL) 
![Stars](https://img.shields.io/github/stars/shengchaochen82/MetePFL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/shengchaochen82/MetePFL?color=critical&style=social) | IJCAI 2023  

| Multivariable |  Hurricane 
  Climate   |   Self-Recover     | [Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage Using Self-Supervised Learning](https://www.ijcai.org/proceedings/2023/4141) | None  | IJCAI 2023  

| Multivariable | Weather 
  Traffc  
 Electricity    
  Exchange   
  ILI   |   SMARTformer     | [SMARTformer: Semi-Autoregressive Transformer with Efficient Integrated Window Attention for Long Time Series Forecasting](https://www.ijcai.org/proceedings/2023/241) | None| IJCAI 2023  

| Multivariable | METR-LA 
 Beijing 
 Xiamen |    INCREASE    | [INCREASE: Inductive Graph Representation Learning for Spatio-Temporal Kriging](https://dl.acm.org/doi/abs/10.1145/3543507.3583525) | [TF](https://github.com/zhengchuanpan/INCREASE) 
![Stars](https://img.shields.io/github/stars/zhengchuanpan/INCREASE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhengchuanpan/INCREASE?color=critical&style=social)  | WWW 2023

| Multivariable | MQPS 
 ETT 
 Electricity |    KAE-Informer    | [KAE-Informer: A Knowledge Auto-Embedding Informer for Forecasting Long-Term Workloads of Microservices](https://doi.org/10.1145/3543507.3583288) | [Pytorch](https://github.com/citsjtu2020/KAE-Informer-MQPS) 
![Stars](https://img.shields.io/github/stars/citsjtu2020/KAE-Informer-MQPS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/citsjtu2020/KAE-Informer-MQPS?color=critical&style=social)  | WWW 2023

| Multivariable | Typhoon-JP 
 COVID-JP 
 Hurricane-US |    MemeSTN    | [Learning Social Meta-knowledge for Nowcasting Human Mobility in Disaster](https://doi.org/10.1145/3543507.3583991) | [Pytorch](https://github.com/citsjtu2020/KAE-Informer-MQPS) 
![Stars](https://img.shields.io/github/stars/citsjtu2020/KAE-Informer-MQPS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/citsjtu2020/KAE-Informer-MQPS?color=critical&style=social)  | WWW 2023

| Multivariable |   NYC  
  Chicago  |  EALGAP   | [Extreme-Aware Local-Global Attention for Spatio-Temporal Urban Mobility Learning](https://ieeexplore.ieee.org/document/10184645) | [Keras](https://github.com/HuiqunHuang/EALGAP) 
![Stars](https://img.shields.io/github/stars/HuiqunHuang/EALGAP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HuiqunHuang/EALGAP?color=critical&style=social) | ICDE 2023  

| Multivariable | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  |  DyHSL   | [Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting](https://ieeexplore.ieee.org/document/10184800) | [Pytorch](https://github.com/YushengZhao/DyHSL) 
![Stars](https://img.shields.io/github/stars/YushengZhao/DyHSL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YushengZhao/DyHSL?color=critical&style=social) | ICDE 2023  

| Multivariable | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  |  STWave   | [When Spatio-Temporal Meet Wavelets: Disentangled Traffic Forecasting via Efficient Spectral Graph Attention Networks](https://ieeexplore.ieee.org/document/10184591) | [Pytorch](https://github.com/LMissher/STWave) 
![Stars](https://img.shields.io/github/stars/LMissher/STWave?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LMissher/STWave?color=critical&style=social) | ICDE 2023  

| Multivariable | Seattle 
 PEMS04  
 PEMS08  |  SSTBAN   | [Self-Supervised Spatial-Temporal Bottleneck Attentive Network for Efficient Long-term Traffic Forecasting](https://ieeexplore.ieee.org/document/10184658) | [Pytorch](https://github.com/guoshnBJTU/SSTBAN) 
![Stars](https://img.shields.io/github/stars/guoshnBJTU/SSTBAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/guoshnBJTU/SSTBAN?color=critical&style=social) | ICDE 2023  

| Multivariable | PEMSD4 
 PEMSD8 
 AirBJ 
 TrafficSIP |   MGTF   | [A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework](https://dl.acm.org/doi/10.1145/3539597.3570396) | [Author](http://home.ustc.edu.cn/~wx309/)  | WSDM 2023

| Multivariable |  METR-LA 
 PEMS-BAY  
 PEMS04 
 PEMS07 
 PEMS08|  STAEformer   | [Spatio-Temporal Adaptive Embedding Makes Vanilla Transformer SOTA for Traffic Forecasting](https://dl.acm.org/doi/10.1145/3583780.3615136) | [Pytorch](https://github.com/XDZhelheim/STAEformer) 
![Stars](https://img.shields.io/github/stars/XDZhelheim/STAEformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/XDZhelheim/STAEformer?color=critical&style=social) | CIKM 2023  

| Traffic | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08 |  TrendGCN   | [Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting](https://dl.acm.org/doi/10.1145/3583780.3614868) | [Pytorch](https://github.com/juyongjiang/TrendGCN) 
![Stars](https://img.shields.io/github/stars/juyongjiang/TrendGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/juyongjiang/TrendGCN?color=critical&style=social) | CIKM 2023  

| Multivariable | ETT 
 Electricity  
 Traffic   
 Weather 
 ILI 
  Exchange |  GCformer   | [GCformer: An Efficient Solution for Accurate and Scalable Long-Term Multivariate Time Series Forecasting](https://dl.acm.org/doi/10.1145/3583780.3614868) | [Pytorch](https://github.com/Yanjun-Zhao/GCformer) 
![Stars](https://img.shields.io/github/stars/Yanjun-Zhao/GCformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Yanjun-Zhao/GCformer?color=critical&style=social) | CIKM 2023  

| Multivariable | ETT 
 Electricity  
 Traffic |  Seq2Peak  | [Unlocking the Potential of Deep Learning in Peak-Hour Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3583780.3615159) | [Pytorch](https://github.com/zhangzw16/Seq2Peak) 
![Stars](https://img.shields.io/github/stars/zhangzw16/Seq2Peak?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhangzw16/Seq2Peak?color=critical&style=social) | CIKM 2023   

| Multivariable |  PEMS04 
  PEMS07  
 PEMS08  
 NYC Crime  
 CHI Crime |  CL4ST  | [Spatio-Temporal Meta Contrastive Learning](https://dl.acm.org/doi/10.1145/3583780.3615065) | [Pytorch](https://github.com/HKUDS/CL4ST) 
![Stars](https://img.shields.io/github/stars/HKUDS/CL4ST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HKUDS/CL4ST?color=critical&style=social) | CIKM 2023  

| Multivariable | NYC Bike  
 NYC Taxi    |  MLPST | [MLPST: MLP is All You Need for Spatio-Temporal Prediction](https://dl.acm.org/doi/10.1145/3583780.3614969) | [Author](https://github.com/Zhang-Zijian)  | CIKM 2023  

| Multivariable | TaxiBJ  
 BikeNYC    |  MC-STL  | [Mask- and Contrast-Enhanced Spatio-Temporal Learning for Urban Flow Prediction](https://dl.acm.org/doi/10.1145/3583780.3614958) | [Pytorch](https://github.com/CodeZx6/MCSTL) 
![Stars](https://img.shields.io/github/stars/CodeZx6/MCSTL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CodeZx6/MCSTL?color=critical&style=social) | CIKM 2023  

| Multivariable | PeMS  
 Beijing  
 Electricity   
 COVID-CHI |  MemDA   | [MemDA: Forecasting Urban Time Series with Memory-based Drift Adaptation](https://dl.acm.org/doi/10.1145/3583780.3615136) | [Pytorch](https://github.com/deepkashiwa20/Urban_Concept_Drift) 
![Stars](https://img.shields.io/github/stars/deepkashiwa20/Urban_Concept_Drift?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/deepkashiwa20/Urban_Concept_Drift?color=critical&style=social) | CIKM 2023  

| Cross City 
 Traffic |   PEMS-BAY  
 METR-LA   
 Chengdu   
   Shenzhen|  TPB  | [Cross-city Few-Shot Traffic Forecasting via Traffic Pattern Bank](https://dl.acm.org/doi/10.1145/3583780.3614829) | [Pytorch](https://github.com/zhyliu00/TPB) 
![Stars](https://img.shields.io/github/stars/zhyliu00/TPB?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhyliu00/TPB?color=critical&style=social) | CIKM 2023  

| Traffic Speed | METR-LA 
 PEMS-BAY  
 PEMSD7M  |  UAGCRN  | [Enhancing Spatio-temporal Traffic Prediction through Urban Human Activity Analysis](https://dl.acm.org/doi/10.1145/3583780.3614867) | [TF](https://github.com/SuminHan/Traffic-UAGCRNTF) 
![Stars](https://img.shields.io/github/stars/SuminHan/Traffic-UAGCRNTF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SuminHan/Traffic-UAGCRNTF?color=critical&style=social) | CIKM 2023  

| Multivariable | Complaint 
 NYC Taxi    |  PromptST  | [PromptST: Prompt-Enhanced Spatio-Temporal Multi-Attribute Prediction](https://dl.acm.org/doi/abs/10.1145/3583780.3615159) | [Pytorch](https://github.com/Zhang-Zijian/PromptST) 
![Stars](https://img.shields.io/github/stars/Zhang-Zijian/PromptST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Zhang-Zijian/PromptST?color=critical&style=social) | CIKM 2023  

| Multivariable | METR-LA 
 PEMS-BAY  
 PEMS08 |  HIEST  | [Rethinking Sensors Modeling: Hierarchical Information Enhanced Traffic Forecasting](https://dl.acm.org/doi/10.1145/3583780.3614910) | [Pytorch](https://github.com/VAN-QIAN/CIKM23-HIEST) 
![Stars](https://img.shields.io/github/stars/VAN-QIAN/CIKM23-HIEST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/VAN-QIAN/CIKM23-HIEST?color=critical&style=social) | CIKM 2023  

| Multivariable | ETT 
 Electricity  
 Weather  
 Traffic |  TemDep  | [TemDep: Temporal Dependency Priority for Multivariate Time Series Prediction](https://dl.acm.org/doi/10.1145/3583780.3615164) | [Pytorch](https://github.com/zivgogogo/TemDep) 
![Stars](https://img.shields.io/github/stars/zivgogogo/TemDep?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zivgogogo/TemDep?color=critical&style=social) | CIKM 2023  

| Traffic |  BJ-Center  
  METR-LA |  ST-MoE  | [ST-MoE: Spatio-Temporal Mixture-of-Experts for Debiasing in Traffic Prediction](https://dl.acm.org/doi/10.1145/3583780.3615068) | None  | CIKM 2023  

| Multivariable | ETT 
 Electricity  
 Weather  
 Traffic  
  Exchange  |  AVGNets  | [Learning Visibility Attention Graph Representation for Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3583780.3615289) | None | CIKM 2023  

| Multivariable |  PEMS03  
 PEMS04 
  PEMS07  
 PEMS08   |  STGBN  | [Spatial-Temporal Graph Boosting Networks: Enhancing Spatial-Temporal Graph Neural Networks via Gradient Boosting](https://dl.acm.org/doi/10.1145/3583780.3615066) | None  | CIKM 2023 

| Multivariable | ETT 
 Electricity  
 Traffic   
 ILI 
  Exchange | FAMC-Net   | [FAMC-Net: Frequency Domain Parity Correction Attention and Multi-Scale Dilated Convolution for Time Series Forecasting](https://dl.acm.org/doi/10.1145/3583780.3614876) | None| CIKM 2023  

| Cross City 
 Traffic |  NYC  
 Chicago    
 Nashville   |  CARPG  | [CARPG: Cross-City Knowledge Transfer for Traffic Accident Prediction via Attentive Region-Level Parameter Generation](https://dl.acm.org/doi/abs/10.1145/3583780.3614802) | None| CIKM 2023  

| Traffic | SPEED 
 FLOW  |  CANet  | [Clustering-property Matters: A Cluster-aware Network for Large Scale Multivariate Time Series Forecasting](https://dl.acm.org/doi/abs/10.1145/3583780.3615253) | None  | CIKM 2023  

| Multivariable | ETT 
 Exchange  
 ILI   
 Weather  
  Electricity  
 Traffic |  DSformer   | [DSformer: A Double Sampling Transformer for Multivariate Time Series Long-term Prediction](https://dl.acm.org/doi/abs/10.1145/3583780.3614851) | None | CIKM 2023 

| Multivariable | Wufu    |  MODE    | [Monotonic Neural Ordinary Differential Equation: Time-series Forecasting for Cumulative Data](https://dl.acm.org/doi/10.1145/3583780.3615487) |  None  | CIKM 2023  

| Multivariable | NYC  |  MetaRSTP  | [Region Profile Enhanced Urban Spatio-Temporal Prediction via Adaptive Meta-Learning](https://dl.acm.org/doi/10.1145/3583780.3615027) |    None  | CIKM 2023  

| Multivariable | SIP 
  NYC  
 METR-LA |    G2S    | [Towards Learning in Grey Spatiotemporal Systems: A Prophet to Non-consecutive Spatiotemporal Dynamics](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch22) | None | SDM 2023

| Multivariable | Solar 
  PEMS-BAY 
 Electricity |    ERL    | [Time-delayed Multivariate Time Series Predictions](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch37) | None | SDM 2023

| Multivariable | Weather2K   |   Weather2K     | [Weather2K: A Multivariate Spatio-Temporal Benchmark Dataset for Meteorological Forecasting Based on Real-Time Observation Data from Ground Weather Stations](https://proceedings.mlr.press/v206/zhu23a.html) | [Weather2K](https://github.com/bycnfz/weather2k/) 
![Stars](https://img.shields.io/github/stars/bycnfz/weather2k?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/bycnfz/weather2k?color=critical&style=social) | AISTATS 2023  

| Multivariable | ETT 
 Electricity  
 Exchange   
 Traffic 
 Weather 
  ILI |    FiLM    | [FiLM: Frequency improved Legendre Memory Model for Long-term Time Series Forecasting](https://openreview.net/forum?id=zTQdHSQUQWc) | [Pytorch](https://github.com/tianzhou2011/FiLM) 
![Stars](https://img.shields.io/github/stars/tianzhou2011/FiLM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tianzhou2011/FiLM?color=critical&style=social) | NeurIPS 2022

| Multivariable | ETT 
 Electricity  
 Exchange  
 Weather |    LaST    | [Learning Latent Seasonal-Trend Representations for Time Series Forecasting](https://openreview.net/forum?id=C9yUwd72yy) | [Pytorch](https://github.com/zhycs/LaST) 
![Stars](https://img.shields.io/github/stars/zhycs/LaST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhycs/LaST?color=critical&style=social) | NeurIPS 2022

| Multivariable | ETT 
 Electricity  
 Exchange  
 Traffic 
 Weather 
  ILI |    WaveBound    | [WaveBound: Dynamic Error Bounds for Stable Time Series Forecasting](https://openreview.net/forum?id=vsNQkquutZk) | [Pytorch](https://github.com/choyi0521/WaveBound) 
![Stars](https://img.shields.io/github/stars/choyi0521/WaveBound?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/choyi0521/WaveBound?color=critical&style=social) | NeurIPS 2022

| Multivariable | COVID-19 
 PEMS04  
 PEMS08  
 Temperature 
 Bytom 
  Wind |    ZFC-SHCN    | [Time-Conditioned Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series Forecasting](https://openreview.net/forum?id=2Ln-TWxVtf) | [Future](https://github.com/zfcshcn/ZFC-SHCN) | NeurIPS 2022

| Multivariable | ETT 
 Traffic  
 Solar  
 Electricity 
 Exchange  
    PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  |    SCINet    | [SCINet: Time Series Modeling and Forecasting with Sample Convolution and Interaction](https://openreview.net/forum?id=AyajSjTAzmg) | [Pytorch](https://github.com/cure-lab/SCINet) 
![Stars](https://img.shields.io/github/stars/cure-lab/SCINet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/cure-lab/SCINet?color=critical&style=social) | NeurIPS 2022

| Multivariable | Electricity 
 ETT  
 Exchange  
  ILI  
 Traffic 
 Weather |   NonstaTransformer   | [Non-stationary Transformers: Exploring the Stationarity in Time Series Forecasting](https://openreview.net/forum?id=ucNDIDRNjjv) | [Pytorch](https://github.com/thuml/Nonstationary_Transformers) 
![Stars](https://img.shields.io/github/stars/thuml/Nonstationary_Transformers?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/Nonstationary_Transformers?color=critical&style=social) | NeurIPS 2022

| Multivariable | Traffic 
 Solar  
 Electricity  
  Exchange  
 PEMS07(M) 
 PEMS-BAY |   TPGNN   | [Multivariate Time-Series Forecasting with Temporal Polynomial Graph Neural Networks](https://openreview.net/forum?id=pMumil2EJh) | [Future](https://github.com/zyplanet/TPGNN) | NeurIPS 2022

| Multivariable | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08  |    DSTAGNN    | [DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting](https://proceedings.mlr.press/v162/lan22a.html) | [Pytorch](https://github.com/SYLan2019/DSTAGNN) 
![Stars](https://img.shields.io/github/stars/SYLan2019/DSTAGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SYLan2019/DSTAGNN?color=critical&style=social) | ICML 2022

| Multivariable | ETT 
 Electricity  
 Exchange  
 Traffic 
 Weather 
 ILI |        FEDformer 
 (EncDec,
 EnhancedFeature)      | [FEDformer: Frequency Enhanced Decomposed Transformer for Long-term Series Forecasting](https://proceedings.mlr.press/v162/zhou22g.html) | [Pytorch](https://github.com/MAZiqing/FEDformer) 
![Stars](https://img.shields.io/github/stars/MAZiqing/FEDformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/MAZiqing/FEDformer?color=critical&style=social) | ICML 2022

| Multivariable | Traffic 
 Electricity  
 Wiki  
 Sales  |       DAF     | [DAF-Domain Adaptation for Time Series Forecasting via Attention Sharing](https://proceedings.mlr.press/v162/jin22d.html) | None| ICML 2022

| Multivariable | Electricity  
 Solar  
 Fred MD 
 KDD Cup  |        TACTiS 
 (Copulas,
 Trans)      | [TACTiS: Transformer-Attentional Copulas for Time Series](https://proceedings.mlr.press/v162/drouin22a.html) | [Pytorch](https://github.com/servicenow/tactis) 
![Stars](https://img.shields.io/github/stars/servicenow/tactis?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/servicenow/tactis?color=critical&style=social) | ICML 2022

| Multivariable | French 
 Electricity    |        AgACI      | [Adaptive Conformal Predictions for Time Series](https://arxiv.org/abs/2202.07282) | [Python,R](https://github.com/mzaffran/AdaptiveConformalPredictionsTimeSeries) 
![Stars](https://img.shields.io/github/stars/mzaffran/AdaptiveConformalPredictionsTimeSeries?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mzaffran/AdaptiveConformalPredictionsTimeSeries?color=critical&style=social) | ICML 2022

| Traffic Speed | NAVER-Seoul 
 METR-LA |   PM-MemNet 
 (Mem,KNN)         | [Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting](https://openreview.net/forum?id=wwDg3bbYBIq) | [Pytorch](https://github.com/HyunWookL/PM-MemNet) 
![Stars](https://img.shields.io/github/stars/HyunWookL/PM-MemNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HyunWookL/PM-MemNet?color=critical&style=social) | ICLR 2022

| Multivariable | PEMS03 
 PEMS04 
 PEMS08 
 COVID-19,etc |         TAMP-S2GCNets 
 (GCN,AR, 
 Topological Features)        | [TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting](https://openreview.net/forum?id=wv6g8fWLX2q) | [Pytorch](https://www.dropbox.com/sh/n0ajd5l0tdeyb80/AABGn-ejfV1YtRwjf_L0AOsNa?dl=0) | ICLR 2022

| Multivariable | ETT 
 Electricity 
 Weather |         CoST         | [CoST: Contrastive Learning of Disentangled Seasonal-Trend Representations for Time Series Forecasting](https://openreview.net/forum?id=PilZY3omXV2) | [Pytorch](https://github.com/salesforce/CoST) 
![Stars](https://img.shields.io/github/stars/salesforce/CoST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/salesforce/CoST?color=critical&style=social) | ICLR 2022

| Multivariable | Electricity 
 Traffic 
 M4 
 CASIO 
 NP |         DEPTS         | [DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting](https://openreview.net/forum?id=AJAR-JgNw__) | [Pytorch](https://github.com/weifantt/DEPTS) 
![Stars](https://img.shields.io/github/stars/weifantt/DEPTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/weifantt/DEPTS?color=critical&style=social) | ICLR 2022

| Multivariable | ETT 
 Electricity 
 Wind 
 App Flow |         Pyraformer     | [Pyraformer: Low-Complexity Pyramidal Attention for Long-Range Time Series Modeling and Forecasting](https://openreview.net/forum?id=0EXmFzUn5I) | [Pytorch](https://github.com/alipay/Pyraformer) 
![Stars](https://img.shields.io/github/stars/alipay/Pyraformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/alipay/Pyraformer?color=critical&style=social) | ICLR 2022

| Multivariable | ETT 
 Electricity  
 M4 
 Air Quality 
 Nasdaq |         RevIN     | [Reversible Instance Normalization for Accurate Time-Series Forecasting against Distribution Shift](https://openreview.net/forum?id=cGDAkQo1C0p) | [Pytorch](https://github.com/ts-kim/RevIN) 
![Stars](https://img.shields.io/github/stars/ts-kim/RevIN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ts-kim/RevIN?color=critical&style=social) | ICLR 2022

| Multivariable | METR-LA 
  PEMS-BAY  
  PEMS04  
  PEMS08   |         D2STGNN     | [Decoupled Dynamic Spatial-Temporal Graph Neural Network for Traffic Forecasting](https://www.vldb.org/pvldb/vol15/p2733-shao.pdf) | [Pytorch](https://github.com/zezhishao/D2STGNN) 
![Stars](https://img.shields.io/github/stars/zezhishao/D2STGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zezhishao/D2STGNN?color=critical&style=social) | VLDB 2022

| Multivariable |  METR-LA 
  PEMS-BAY  
  PEMS04   |         STEP     | [Pre-training Enhanced Spatial-temporal Graph Neural Network for Multivariate Time Series Forecasting](https://doi.org/10.1145/3534678.3539396) | [Pytorch](https://github.com/zezhishao/STEP) 
![Stars](https://img.shields.io/github/stars/zezhishao/STEP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zezhishao/STEP?color=critical&style=social) | KDD 2022

| Multivariable | Solar 
  Electricity  
  Exchange  
  Wind 
  NYCBike 
  NYCTaxi   |         ESG     | [Learning the Evolutionary and Multi-scale Graph Structure for Multivariate Time Series Forecasting](https://doi.org/10.1145/3534678.3539274) | [Pytorch](https://github.com/LiuZH-19/ESG) 
![Stars](https://img.shields.io/github/stars/LiuZH-19/ESG?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LiuZH-19/ESG?color=critical&style=social) | KDD 2022

| Multivariable | METR-LA 
  Solar  
  Traffic 
 ECG5000  |         VSF     | [Multi-Variate Time Series Forecasting on Variable Subsets](https://doi.org/10.1145/3534678.3539394) | [Pytorch,dgl](https://github.com/google/vsf-time-series) 
![Stars](https://img.shields.io/github/stars/google/vsf-time-series?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/google/vsf-time-series?color=critical&style=social) | KDD 2022

| Multivariable | DC Bike 
  DC Taxi  |         CrossTReS     | [Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting](https://doi.org/10.1145/3534678.3539250) | [Pytorch,dgl](https://github.com/KL4805/CrossTReS) 
![Stars](https://img.shields.io/github/stars/KL4805/CrossTReS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/KL4805/CrossTReS?color=critical&style=social) | KDD 2022

| Multivariable |  ETT 
 Weather 
 Exchange 
 Traffic 
 Electricity |         Quatformer     | [Learning to Rotate: Quaternion Transformer for Complicated Periodical Time Series Forecasting](https://doi.org/10.1145/3534678.3539234) | [MRA-BGCN Author](https://scholar.google.com/citations?hl=zh-CN&user=dMg_soMAAAAJ&view_op=list_works&sortby=pubdate) 
 None Code | KDD 2022

| Multivariable | NYCBike 
  NYCTaxi  
  PEMS03  
  PEMS08 |         GMSDR     | [MSDR: Multi-Step Dependency Relation Networks for Spatial Temporal Forecasting](https://doi.org/10.1145/3534678.3539397) | [Pytorch](https://github.com/dcliu99/MSDR) 
![Stars](https://img.shields.io/github/stars/dcliu99/MSDR?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/dcliu99/MSDR?color=critical&style=social) | KDD 2022

| Multivariable | Hangzhou 
  NYC   |         DTIGNN     | [Modeling Network-level Traffic Flow Transitions on Sparse Data](https://doi.org/10.1145/3534678.3539236) | [Pytorch](https://github.com/shawlen/dtignn) 
![Stars](https://img.shields.io/github/stars/shawlen/dtignn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/shawlen/dtignn?color=critical&style=social) | KDD 2022

| Multivariable | Temperature 
 Cloud cover  
 Humidity 
 Wind |         CLCRN     | [Conditional Local Convolution for Spatio-temporal Meteorological Forecasting](https://aaai-2022.virtualchair.net/poster_aaai1716) | [Pytorch](https://github.com/BIRD-TAO/CLCRN) 
![Stars](https://img.shields.io/github/stars/BIRD-TAO/CLCRN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BIRD-TAO/CLCRN?color=critical&style=social) | AAAI 2022

| Traffic Flow | PEMS03 
 PEMS04 
 PEMS07 
 PEMS08 
 PEMS07(M) 
 PEMS07(L) |         STG-NCDE     | [Graph Neural Controlled Differential Equations for Traffic Forecasting](https://aaai-2022.virtualchair.net/poster_aaai6502) | [Pytorch](https://github.com/jeongwhanchoi/STG-NCDE) 
![Stars](https://img.shields.io/github/stars/jeongwhanchoi/STG-NCDE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/jeongwhanchoi/STG-NCDE?color=critical&style=social) | AAAI 2022

| Traffic Flow  | GT-221 
 WRS-393 
 ZGC-564 |         STDEN     | [STDEN: Towards Physics-guided Neural Networks for Traffic Flow Prediction](https://aaai-2022.virtualchair.net/poster_aaai211) | [Pytorch](https://github.com/Echo-Ji/STDEN)   
![Stars](https://img.shields.io/github/stars/Echo-Ji/STDEN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Echo-Ji/STDEN?color=critical&style=social) | AAAI 2022

| Multivariable | Electricity 
 Traffic 
 PEMS07(M) 
 METR-LA  |         CATN     | [CATN: Cross Attentive Tree-Aware Network for Multivariate Time Series Forecasting](https://aaai-2022.virtualchair.net/poster_aaai7403) | None | AAAI 2022

| Multivariable | ETT 
 Electricity  |         TS2Vec     | [TS2Vec: Towards Universal Representation of Time Series](https://aaai-2022.virtualchair.net/poster_aaai8809) | [Pytorch](https://github.com/yuezhihan/ts2vec) 
![Stars](https://img.shields.io/github/stars/yuezhihan/ts2vec?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yuezhihan/ts2vec?color=critical&style=social) | AAAI 2022

| Multivariable | ETT 
 Electricity 
  Weather |        Triformer       | [Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Full Version](https://doi.org/10.24963/ijcai.2022/277) |  [Pytorch](https://github.com/razvanc92/triformer)  
![Stars](https://img.shields.io/github/stars/razvanc92/triformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/razvanc92/triformer?color=critical&style=social)   | IJCAI 2022

| Multivariable | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08 |        FOGS       | [FOGS: First-Order Gradient Supervision with Learning-based Graph for Traffic Flow Forecasting](https://doi.org/10.24963/ijcai.2022/545) |  [Pytorch](https://github.com/kevin-xuan/FOGS)   
![Stars](https://img.shields.io/github/stars/kevin-xuan/FOGS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/kevin-xuan/FOGS?color=critical&style=social) | IJCAI 2022

| Multivariable | PEMS04 
 PEMS08 
  RPCM  |        RGSL       | [Regularized Graph Structure Learning with Semantic Knowledge for Multi-variates Time-Series Forecasting](https://doi.org/10.24963/ijcai.2022/328) |  [Pytorch](https://github.com/alipay/RGSL)   
![Stars](https://img.shields.io/github/stars/alipay/RGSL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/alipay/RGSL?color=critical&style=social) | IJCAI 2022

| Multivariable | Air Quality 
 Parking  |       DMGA      | [Long-term Spatio-Temporal Forecasting via Dynamic Multiple-Graph Attention](https://doi.org/10.24963/ijcai.2022/309) |   None  | IJCAI 2022

| Multivariable | YellowCab 
 GreenCab 
 Solar  |        ST-KMRN       | [Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data](https://doi.org/10.24963/ijcai.2022/304) |   [Author](https://github.com/mengcz13)   | IJCAI 2022

| Multivariable | NYCTaxi 
 NYCBike 
  CHIBike  
  BJTaxi 
 Chengdu|        STAN       | [When Transfer Learning Meets Cross-City Urban Flow Prediction: Spatio-Temporal Adaptation Matters](https://doi.org/10.24963/ijcai.2022/282) | None | IJCAI 2022

| Multivariable | Hurricanes 
 Ausgrid 
  Weather |        DeepExtrema       | [DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data](https://doi.org/10.24963/ijcai.2022/413) |  [Pytorch](https://github.com/galib19/DeepExtrema-IJCAI22-)   
![Stars](https://img.shields.io/github/stars/galib19/DeepExtrema-IJCAI22-?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/galib19/DeepExtrema-IJCAI22-?color=critical&style=social) | IJCAI 2022

| Multivariable | GoogleSymptoms  
 Covid19  
 Power 
 Tweet |         CAMul     | [CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting](https://doi.org/10.1145/3485447.3512037) |  [Pytorch](https://github.com/AdityaLab/CAMul)  
![Stars](https://img.shields.io/github/stars/AdityaLab/CAMul?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AdityaLab/CAMul?color=critical&style=social) | WWW 2022

| Multivariable | Electricity 
 Stock  |         MRLF     | [Multi-Granularity Residual Learning with Confidence Estimation for Time Series Prediction](https://doi.org/10.1145/3485447.3512056) | [Pytorch](https://github.com/CMLF-git-dev/MRLF) 
![Stars](https://img.shields.io/github/stars/CMLF-git-dev/MRLF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CMLF-git-dev/MRLF?color=critical&style=social) | WWW 2022

| Multivariable 
 Classification 
 Forecasting | MuJoCo  
 Google Stock  |         EXIT     | [EXIT: Extrapolation and Interpolation-based Neural Controlled Differential Equations for Time-series Classification and Forecasting](https://doi.org/10.1145/3485447.3512030) | [Pytorch](https://github.com/sheoyon-jhin/EXIT) 
![Stars](https://img.shields.io/github/stars/sheoyon-jhin/EXIT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sheoyon-jhin/EXIT?color=critical&style=social) | WWW 2022

| Traffic Flow | PEMS03 
 PEMS04 
  PEMS07  
 PEMS08 |   ST-WA    | [Towards Spatio- Temporal Aware Traffic Time Series Forecasting](https://ieeexplore.ieee.org/document/9835586) | [Pytorch](https://github.com/razvanc92/ST-WA) 
![Stars](https://img.shields.io/github/stars/razvanc92/ST-WA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/razvanc92/ST-WA?color=critical&style=social) | ICDE 2022

| Mobility 
 Prediction  | NYC 
 Dallas  
  Miami  |       SHIFT   | [Translating Human Mobility Forecasting through Natural Language Generation](https://doi.org/10.1145/3488560.3498387) | [Hao Xue](https://github.com/xuehaouwa) | WSDM 2022

| Traffic Flow | TaxiBJ 
 BikeNYC |         ST-GSP     | [ST-GSP: Spatial-Temporal Global Semantic Representation Learning for Urban Flow Prediction](https://dl.acm.org/doi/abs/10.1145/3488560.3498444) | [Pytorch](https://github.com/k51/STGSP) 
![Stars](https://img.shields.io/github/stars/k51/STGSP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/k51/STGSP?color=critical&style=social) | WSDM 2022

|  Multivariable | Traffic 
 Temperature |      ReTime   | [Retrieval Based Time Series Forecasting](https://arxiv.org/abs/2209.13525#) | None| CIKM 2022

|  Multivariable | Rainfall 
 Traffic  
 ETT 
 Stock 
 Climate   |      DXtreMM   | [Deep Extreme Mixture Model for Time Series Forecasting](https://doi.org/10.1145/3511808.3557282) |  [Pytorch](https://github.com/DXtreMM/DXtreMM_TSF) 
![Stars](https://img.shields.io/github/stars/DXtreMM/DXtreMM_TSF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DXtreMM/DXtreMM_TSF?color=critical&style=social) | CIKM 2022

|  MTS Analysis 
 MTS Forecasting 
 Anormaly Detection | ETT 
 Electricity  
 SMD 
 SMAP 
 MSL 
 SWaT  |      MARINA   | [MARINA: An MLP-Attention Model for Multivariate Time-Series](https://doi.org/10.1145/3511808.3557386) |  None| CIKM 2022

| Traffic Speed | METR-LA 
  PEMS-BAY   |      ResCAL   | [Residual Correction in Real-Time Traffic Forecasting](https://doi.org/10.1145/3511808.3557432) |  None | CIKM 2022

| Model Selection |     |      AutoForecast   | [AutoForecast: Automatic Time-Series Forecasting Model Selection](https://doi.org/10.1145/3511808.3557241) | None | CIKM 2022

|   Traffic Flow |  PEMS04 
  PEMS07  
 PEMS08    |      DastNet   | [Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities](https://doi.org/10.1145/3511808.3557294) |  [Pytorch](https://github.com/YihongT/DASTNet) 
![Stars](https://img.shields.io/github/stars/YihongT/DASTNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YihongT/DASTNet?color=critical&style=social) | CIKM 2022

|   Traffic Flow & Speed | METR-LA 
  PEMS-BAY 
   PEMS03 
  PEMS04 
  PEMS07  
 PEMS08    |      AutoSTS   | [Automated Spatio-Temporal Synchronous Modeling with Multiple Graphs for Traffic Prediction](https://doi.org/10.1145/3511808.3557243) | YongLi THU | CIKM 2022

|   Traffic Condition |  TRCV-BJ 
  TRCV-SH  
 TRCV-ZZ    |      DuTraffic   | [DuTraffic: Live Traffic Condition Prediction with Trajectory Data and Street Views at Baidu Maps](https://doi.org/10.1145/3511808.3557151) |  None | CIKM 2022

|  Multivariable  | ETT 
 Electricity 
 WTH 
 Weather 
 ILI  
 Exchange  |      Linear   | [Do Simpler Statistical Methods Perform Better in Multivariate Long Sequence Time-Series Forecasting?](https://doi.org/10.1145/3511808.3557585) |  None | CIKM 2022

|  Multivariable  | Solar 
 Traffic 
 Electricity 
 Exchange |      MAGL   | [Memory Augmented Graph Learning Networks for Multivariate Time Series Forecasting](https://doi.org/10.1145/3511808.3557638) |  None | CIKM 2022

|  Multivariable  | PEMS04 
  PEMS07  
 PEMS08 
  PEMS-BAY   
 Electricity |      STID   | [Spatial-Temporal Identity: A Simple yet Effective Baseline for Multivariate Time Series Forecasting](https://doi.org/10.1145/3511808.3557702) |  [Pytorch](https://github.com/zezhishao/STID) 
![Stars](https://img.shields.io/github/stars/zezhishao/STID?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zezhishao/STID?color=critical&style=social) | CIKM 2022

|  Multivariable  |  METR-LA 
  PEMS-BAY   
 PEMS04 
 PEMS07 |      ASTTN   | [Adaptive Graph Spatial-Temporal Transformer Network for Traffic Forecasting](https://dl.acm.org/doi/abs/10.1145/3511808.3557540) | None | CIKM 2022

|  Multivariable  | Seoul  |      CGAN   | [Context-aware Traffic Flow Forecasting in New Roads](https://doi.org/10.1145/3511808.3557566) | None | CIKM 2022

|   Traffic Flow & Speed  | METR-LA 
  PEMS-BAY   
 PEMS-M  
  PEMS04 
 PEMS08  |      ST-GAT   | [ST-GAT: A Spatio-Temporal Graph Attention Network for Accurate Traffic Speed Prediction](https://doi.org/10.1145/3511808.3557705) | [Author](https://github.com/Hanyang-HCC-Lab) | CIKM 2022

|   Traffic Speed  | METR-LA 
  PEMS-BAY |     HOMGNNs   | [Higher-Order Masked Graph Neural Networks for Traffic Flow Prediction](https://ieeexplore.ieee.org/document/10027720) | [Pytorch](https://github.com/maisuiqianxun/HOMGNN) 
![Stars](https://img.shields.io/github/stars/maisuiqianxun/HOMGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/maisuiqianxun/HOMGNN?color=critical&style=social) | ICDM 2022

| Multivariable | M4 
 Electricity 
 car-parts  |         TopAttn     | [Topological Attention for Time Series Forecasting](https://NeurIPS.cc/Conferences/2021/ScheduleMultitrack?event=26763) | [Pytorch](https://github.com/plus-rkwitt/TAN)
 
![Stars](https://img.shields.io/github/stars/plus-rkwitt/TAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/plus-rkwitt/TAN?color=critical&style=social) Future | NeurIPS 2021

| Multivariable | Rossmann 
 M5 
 Wiki  |         MisSeq     | [MixSeq: Connecting Macroscopic Time Series Forecasting with Microscopic Time Series Data](https://proceedings.neurips.cc/paper/2021/hash/6b5754d737784b51ec5075c0dc437bf0-Abstract.html) | None | NeurIPS 2021

| Multivariable | ETT 
 Electricity 
 Exchange 
 Traffic 
 Weather 
 ILI |         Autoformer     | [Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting](https://openreview.net/forum?id=J4gRj6d5Qm) | [Pytorch](https://github.com/thuml/Autoformer) 
![Stars](https://img.shields.io/github/stars/thuml/Autoformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuml/Autoformer?color=critical&style=social) | NeurIPS 2021

| Multivariable | PEMS04 
 PEMS08 
 Traffic 
 ADI 
 M4 ,etc |         Error     | [Adjusting for Autocorrelated Errors in Neural Networks for Time Series](https://openreview.net/forum?id=tJ_CO8orSI) | [Pytorch](https://github.com/Daikon-Sun/AdjustAutocorrelation) 
![Stars](https://img.shields.io/github/stars/Daikon-Sun/AdjustAutocorrelation?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Daikon-Sun/AdjustAutocorrelation?color=critical&style=social) | NeurIPS 2021

| Multivariable | Bytom 
 Decentraland 
  PEMS04 
 PEMS08|         Z-GCNETs     | [Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting](http://proceedings.mlr.press/v139/chen21o.html) | [Pytorch](https://github.com/Z-GCNETs/Z-GCNETs) 
![Stars](https://img.shields.io/github/stars/Z-GCNETs/Z-GCNETs?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Z-GCNETs/Z-GCNETs?color=critical&style=social) | ICML 2021

| Multivariable | PEMS07(M) 
 METR-LA 
  PEMS-BAY  |         Cov     | [Conditional Temporal Neural Processes with Covariance Loss](http://proceedings.mlr.press/v139/yoo21b.html) | None | ICML 2021

| Multivariable | METR-LA 
  PEMS-BAY  
  PMU |         GTS     | [Discrete Graph Structure Learning for Forecasting Multiple Time Series](https://openreview.net/forum?id=WEHSlH5mOk) | [Pytorch](https://github.com/chaoshangcs/GTS) 
![Stars](https://img.shields.io/github/stars/chaoshangcs/GTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chaoshangcs/GTS?color=critical&style=social) | ICLR 2021

| Multivariable | Benz 
 Air Quality 
 FuelMoisture  |         framework     | [A Transformer-based Framework for Multivariate Time Series Representation Learning](https://doi.org/10.1145/3447548.3467401) | [Pytorch](https://github.com/gzerveas/mvts_transformer)  
![Stars](https://img.shields.io/github/stars/gzerveas/mvts_transformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gzerveas/mvts_transformer?color=critical&style=social) | KDD 2021

| Federated Multivariable | PEMS-BAY 
  METR-LA  |         CNFGNN     | [Cross-Node Federated Graph Neural Network for Spatio-Temporal Data Modeling](https://doi.org/10.1145/3447548.3467371) | [Pytorch](https://github.com/mengcz13/KDD2021_CNFGNN)  
![Stars](https://img.shields.io/github/stars/mengcz13/KDD2021_CNFGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mengcz13/KDD2021_CNFGNN?color=critical&style=social) | KDD 2021

| Traffic Speed  | PEMS04 
  PEMS08 
  England |         DMSTGCN     | [Dynamic and Multi-faceted Spatio-temporal Deep Learning for Traffic Speed Forecasting](https://doi.org/10.1145/3447548.3467275) | [Pytorch](https://github.com/liangzhehan/DMSTGCN)  
![Stars](https://img.shields.io/github/stars/liangzhehan/DMSTGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liangzhehan/DMSTGCN?color=critical&style=social) | KDD 2021

| Traffic Flow  | PEMS07(M) 
  PEMS07(L) 
 PEMS03 
 PEMS04 
 PEMS07 
 PEMS08 |         STGODE     | [Spatial-Temporal Graph ODE Networks for Traffic Flow Forecasting](https://doi.org/10.1145/3447548.3467430) | [Pytorch](https://github.com/square-coder/STGODE)  
![Stars](https://img.shields.io/github/stars/square-coder/STGODE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/square-coder/STGODE?color=critical&style=social) | KDD 2021

| Multivariable  | BikeNYC 
  PEMS07(M) 
 Electricity |        ST-Norm     | [ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting](https://doi.org/10.1145/3447548.3467330) | [Pytorch](https://github.com/JLDeng/ST-Norm)  
![Stars](https://img.shields.io/github/stars/JLDeng/ST-Norm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JLDeng/ST-Norm?color=critical&style=social) | KDD 2021

| Multivariable  | DiDiXM 
  DiDiCD |       TrajNet    | [TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction](https://doi.org/10.1145/3447548.3467236) | None | KDD 2021

| Robust Forecasting  | MIMIC-III 
 USHCN 
 KDD-CUP |      DGM    | [Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/16145) |  [Pytorch](https://github.com/thuwuyinjun/DGM2) 
![Stars](https://img.shields.io/github/stars/thuwuyinjun/DGM2?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuwuyinjun/DGM2?color=critical&style=social) | AAAI 2021

| Multivariable  | Guangzhou 
 Seattle 
 HZMetro , etc. |      DSARF    | [Deep Switching Auto-Regressive Factorization: Application to Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/16907) |  [Pytorch](https://github.com/ostadabbas/DSARF) 
![Stars](https://img.shields.io/github/stars/ostadabbas/DSARF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ostadabbas/DSARF?color=critical&style=social) | AAAI 2021

|Traffic Speed   |  METR-LA  
 PEMS-BAY |      FC-GAGA    | [FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/17114) |  [TF](https://github.com/boreshkinai/fc-gaga) 
![Stars](https://img.shields.io/github/stars/boreshkinai/fc-gaga?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/boreshkinai/fc-gaga?color=critical&style=social) | AAAI 2021

|Traffic Speed   |  DiDiJiNan  
 DiDiXiAn |     HGCN   | [Hierarchical Graph Convolution Network for Traffic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/16088) | [Pytorch](https://github.com/guokan987/HGCN) 
![Stars](https://img.shields.io/github/stars/guokan987/HGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/guokan987/HGCN?color=critical&style=social) | AAAI 2021

|  Multivariable   |  ETT  
 Weather 
 Electricity  |     Informer   | [Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/17325) | [Pytorch](https://github.com/zhouhaoyi/Informer2020) 
![Stars](https://img.shields.io/github/stars/zhouhaoyi/Informer2020?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhouhaoyi/Informer2020?color=critical&style=social) | AAAI 2021

|  Traffic Flow    |  NYCMetro  
 NYC Bike 
 NYC Taxi  |     MOTHER   | [Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/16603) |  None  | AAAI 2021

|  Multivariable  |  METR-LA  
 PEMS-BAY  
 PEMS07(M) 
  PEMS07(L) 
 PEMS03 
 PEMS04 
 PEMS07 
 PEMS08  |     STFGNN   | [Spatial-Temporal Fusion Graph Neural Networks for Traffic Flow Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/16542) | [Mxnet](https://github.com/MengzhangLI/STFGNN) 
![Stars](https://img.shields.io/github/stars/MengzhangLI/STFGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/MengzhangLI/STFGNN?color=critical&style=social) | AAAI 2021

|  Multivariable  | BJ Taxi 
 NYC Taxi  
 NYC Bike1  
 NYC Bike2 |     STGDN   | [Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network](https://ojs.aaai.org/index.php/AAAI/article/view/17761) | [Mxnet](https://github.com/nimingniming/gdn) 
![Stars](https://img.shields.io/github/stars/nimingniming/gdn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nimingniming/gdn?color=critical&style=social) | AAAI 2021

|   Traffic Flow     |  SG-TAXI   |     TrGNN   | [Traffic Flow Prediction with Vehicle Trajectories](https://ojs.aaai.org/index.php/AAAI/article/view/16104) | [Pytorch](https://github.com/mingqian000/TrGNN) 
![Stars](https://img.shields.io/github/stars/mingqian000/TrGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mingqian000/TrGNN?color=critical&style=social) | AAAI 2021

|  Multivariable  | Road 
 POIs 
 SIGtraf |     DMLM   | [Predicting Traffic Congestion Evolution: A Deep Meta Learning Approach](https://www.ijcai.org/proceedings/2021/0417.pdf) | [Future](https://github.com/HelenaYD/DMLM) | IJCAI 2021

|  Multivariable  |  East Bay 
 METR-LA  
 US |     D-DA-GRNN   | [EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting](https://ieeexplore.ieee.org/abstract/document/9458855) | [Pytorch](https://github.com/razvanc92/EnhanceNet) 
![Stars](https://img.shields.io/github/stars/razvanc92/EnhanceNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/razvanc92/EnhanceNet?color=critical&style=social) | ICDE 2021

|  Multivariable  |  Water  
 Humidity  
 Wind, etc |    EA-DRL   | [An Actor-Critic Ensemble Aggregation Model for Time-Series Forecasting](https://ieeexplore.ieee.org/abstract/document/9458798) | None | ICDE 2021

|  Traffic Flow  |  TaxiBJ  
 DiDiCD  
 TaxiRome |    AttConvLSTM   | [Modeling Citywide Crowd Flows using Attentive Convolutional LSTM](https://ieeexplore.ieee.org/document/9458664) | None | ICDE 2021

|  Traffic Speed 
 Traffic Flow  |   METR-LA  
 PEMS-BAY 
 eMS03 
 PEMS04 
 PEMS07 
 PEMS08...|   Benchmark   | [An Empirical Experiment on Deep Learning Models for Predicting Traffic Data](https://ieeexplore.ieee.org/document/9458663) | [Future](https://github.com/HyunWookL/An-Empirical-Experiment-on-Deep-Learning-Models-for-Predicting-Traffic-Data) | ICDE 2021

|  Multivariable  | Motes 
 Soil  
 Revenue  
 Traffic  
 20CR |     NET   | [Network of Tensor Time Series](https://doi.org/10.1145/3442381.3449969) | [Pytorch](https://github.com/baoyujing/NET3) 
![Stars](https://img.shields.io/github/stars/baoyujing/NET3?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/baoyujing/NET3?color=critical&style=social) | WWW 2021

|  Multivariable  | VevoMusic 
 WikiTraffic  
 LOS-LOOP  
 SZ-taxi  |     Radflow   | [Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series](https://doi.org/10.1145/3442381.3449945) | [Pytorch](https://github.com/alasdairtran/radflow) 
![Stars](https://img.shields.io/github/stars/alasdairtran/radflow?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/alasdairtran/radflow?color=critical&style=social) | WWW 2021

|  Multivariable  |  METR-LA  
 Wiki-EN    |     REST   | [REST: Reciprocal Framework for Spatiotemporal-coupled Predictions](https://doi.org/10.1145/3442381.3449928) | None | WWW 2021

|  Multivariable  |  PEMS03 
 PEMS04 
 PEMS07 
 PEMS08   
 HZMetro  |     ASTGNN   | [Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting](https://ieeexplore.ieee.org/document/9346058) | [Pytorch](https://github.com/guoshnBJTU/ASTGNN) 
![Stars](https://img.shields.io/github/stars/guoshnBJTU/ASTGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/guoshnBJTU/ASTGNN?color=critical&style=social) | TKDE 2021

| Multivariable | TaxiBJ  
 BikeNYC-I  
 BikeNYC-II 
 TaxiNYC 
 METR-LA  
 PEMS-BAY  
 PEMS07(M)   |        DL-Traff     | [DL-Traff: Survey and Benchmark of Deep Learning Models for Urban Traffic Prediction](https://doi.org/10.1145/3459637.3482000) | Graph:[PyTorch](https://github.com/deepkashiwa20/DL-Traff-Graph) 
 Grid:[TF](https://github.com/deepkashiwa20/DL-Traff-Grid)  
![Stars](https://img.shields.io/github/stars/deepkashiwa20/DL-Traff-Graph?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/deepkashiwa20/DL-Traff-Graph?color=critical&style=social) | CIKM 2021

| Multivariable | METR-LA  
 PEMS-BAY  
 PEMS07(M)   |        TorchGeoTem  | [PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models](https://doi.org/10.1145/3459637.3482000) | [PyTorch](https://github.com/benedekrozemberczki/pytorch_geometric_temporal)  | CIKM 2021

| Traffic Flow | TaxiBJ 
 BikeNYC |         LLF     | [Learning to Learn the Future: Modeling Concept Drifts in Time Series Prediction](https://doi.org/10.1145/3459637.3482271) | None | CIKM 2021

| Multivariable | ETT 
 Electricity |         HI     | [Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting](https://doi.org/10.1145/3459637.3482120) | None | CIKM 2021

| Multivariable | ETT 
 ELE  |         AGCNT     | [AGCNT: Adaptive Graph Convolutional Network for Transformer-based Long Sequence Time-Series Forecasting](https://doi.org/10.1145/3459637.3482054) | None | CIKM 2021

| Cellular Traffic | cellular   |         MPGAT     | [Multivariate and Propagation Graph Attention Network for Spatial-Temporal Prediction with Outdoor Cellular Traffic](https://doi.org/10.1145/3459637.3482152) | [Pytorch](https://github.com/cylin-cmlab/MPNet)  
![Stars](https://img.shields.io/github/stars/cylin-cmlab/MPNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/cylin-cmlab/MPNet?color=critical&style=social) 
 Future | CIKM 2021

| Traffic Speed | METR-LA 
 PEMS-BAY 
 Simulated |         STNN     | [Space Meets Time: Local Spacetime Neural Network For Traffic Flow Forecasting](https://ieeexplore.ieee.org/abstract/document/9679008/) | [Pytorch](https://github.com/songyangco/STNN) 
![Stars](https://img.shields.io/github/stars/songyangco/STNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/songyangco/STNN?color=critical&style=social) | ICDM 2021

| Traffic Speed | DiDiCD 
 DiDiXiAn  |         T-wave     | [Trajectory WaveNet: A Trajectory-Based Model for Traffic Forecasting](https://ieeexplore.ieee.org/abstract/document/9679147) | [Pytorch](https://github.com/songyangco/STNN) 
![Stars](https://img.shields.io/github/stars/songyangco/STNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/songyangco/STNN?color=critical&style=social) | ICDM 2021

| Multivariable | Sanyo 
 Hanergy 
 Solar 
 Electricity  
 Exchange  |         SSDNet     | [SSDNet: State Space Decomposition Neural Network for Time Series Forecasting](https://ieeexplore.ieee.org/abstract/document/9679135/) | [Pytorch](https://github.com/YangLIN1997/SSDNet-ICDM2021) 
![Stars](https://img.shields.io/github/stars/YangLIN1997/SSDNet-ICDM2021?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YangLIN1997/SSDNet-ICDM2021?color=critical&style=social) | ICDM 2021

| Traffic Volumn | HangZhou City 
 JiNan City |         CTVI     | [Temporal Multi-view Graph Convolutional Networks for Citywide Traffic Volume Inference](https://ieeexplore.ieee.org/abstract/document/9679045/) | [Pytorch](https://github.com/dsj96/CTVI-master) 
![Stars](https://img.shields.io/github/stars/dsj96/CTVI-master?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/dsj96/CTVI-master?color=critical&style=social) | ICDM 2021

| Traffic Volumn | Uber Movements 
  Grab-Posisi |         TEST-GCN     | [TEST-GCN: Topologically Enhanced Spatial-Temporal Graph Convolutional Networks for Traffic Forecasting](https://ieeexplore.ieee.org/abstract/document/9679077) | None | ICDM 2021

| Multivariable | Air Quality City 
 Meterology |         ATGCN     | [Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction](https://doi.org/10.1145/3437963.3441731) | None | WSDM 2021

| Traffic Flow |  WalkWLA  
  BikeNYC   
  TaxiNYC |         PDSTN     | [Predicting Crowd Flows via Pyramid Dilated Deeper Spatial-temporal Network](https://doi.org/10.1145/3437963.3441785) | None | WSDM 2021

| Traffic Flow | PEMS04 
 PEMS08    |         AGCRN        | [Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting](https://proceedings.neurips.cc/paper/2020/hash/ce1aad92b939420fc17005e5461e6f48-Abstract.html) | [Pytorch](https://github.com/LeiBAI/AGCRN) 
![Stars](https://img.shields.io/github/stars/LeiBAI/AGCRN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LeiBAI/AGCRN?color=critical&style=social) | NeurIPS 2020

| Multivariable | Electricity 
 Traffic  
  Wind 
  Solar 
  M4-Hourly  |         AST        | [Adversarial Sparse Transformer for Time Series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/c6b8c8d762da15fa8dbbdfb6baf9e260-Abstract.html) | [Pytorch](https://github.com/hihihihiwsf/AST) 
![Stars](https://img.shields.io/github/stars/hihihihiwsf/AST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hihihihiwsf/AST?color=critical&style=social) | NeurIPS 2020

| Multivariable |  METR-LA 
 PEMS-BAY  
  PEMS07 
  PEMS03 
 PEMS04 ,etc |         StemGNN        | [Spectral Temporal Graph Neural Network for Multivariate Time-series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/cdf6581cb7aca4b7e19ef136c6e601a5-Abstract.html) | [Pytorch](https://github.com/microsoft/StemGNN) 
![Stars](https://img.shields.io/github/stars/microsoft/StemGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/microsoft/StemGNN?color=critical&style=social) | NeurIPS 2020

| Multivariable | M4 
 M3 
 Tourism |         N-BEATS         | [N-BEATS: Neural basis expansion analysis for interpretable time series forecasting](https://openreview.net/forum?id=r1ecqn4YwB) | [Pytorch+Keras](https://github.com/philipperemy/n-beats) 
![Stars](https://img.shields.io/github/stars/philipperemy/n-beats?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/philipperemy/n-beats?color=critical&style=social) | ICLR 2020

| Traffic Flow | Traffic 
 Energy 
 Electricity 
 Exchange  
 METR-LA 
 PEMS-BAY   |         MTGNN        | [Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks](https://dl.acm.org/doi/10.1145/3394486.3403118) | [Pytorch](https://github.com/nnzhan/MTGNN) 
![Stars](https://img.shields.io/github/stars/nnzhan/MTGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nnzhan/MTGNN?color=critical&style=social) | KDD 2020

| Traffic Flow | Taxi-NYC 
 Bike-NYC 
 CTM |         DSAN        | [Preserving Dynamic Attention for Long-Term Spatial-Temporal Prediction](https://doi.org/10.1145/3394486.3403118) | [TF](https://github.com/haoxingl/DSAN) 
![Stars](https://img.shields.io/github/stars/haoxingl/DSAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/haoxingl/DSAN?color=critical&style=social) | KDD 2020

| Traffic Speed 
 Traffic Flow | Shenzhen  |         Curb-GAN        | [Curb-GAN: Conditional Urban Traffic Estimation through Spatio-Temporal Generative Adversarial Networks](https://doi.org/10.1145/3394486.3403127) | [Pytorch](https://github.com/Curb-GAN/Curb-GAN) 
![Stars](https://img.shields.io/github/stars/Curb-GAN/Curb-GAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Curb-GAN/Curb-GAN?color=critical&style=social) | KDD 2020

| Traffic Flow | TaxiBJ 
 CrowdBJ  
 TaxiJN  
 TaxiGY |        AutoST        | [AutoST: Efficient Neural Architecture Search for Spatio-Temporal Prediction](https://doi.org/10.1145/3394486.3403122) | None | KDD 2020

| Traffic Volumn | W3-715 
 E5-2907 |         HSTGCN        | [Hybrid Spatio-Temporal Graph Convolutional Network: Improving Traffic Prediction with Navigation Data](https://doi.org/10.1145/3394486.3403358) | None | KDD 2020

| Multivariable| Xiamen 
 PEMS-BAY  |        GMAN        | [GMAN: A Graph Multi-Attention Network for Traffic Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5477) | [TF](https://github.com/zhengchuanpan/GMAN)
  
![Stars](https://img.shields.io/github/stars/zhengchuanpan/GMAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhengchuanpan/GMAN?color=critical&style=social) [Pytorch](https://github.com/VincLee8188/GMAN-PyTorch) | AAAI 2020

| Multivariable | PEMS03 
 PEMS04 
 PEMS07 
 PEMS08 |      STSGCN       | [Spatial-temporal synchronous graph convolutional networks: A new framework for spatial-temporal network data forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/5438) |  [Mxnet](https://github.com/Davidham3/STSGCN) 
![Stars](https://img.shields.io/github/stars/Davidham3/STSGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Davidham3/STSGCN?color=critical&style=social) 
  [Pytorch](https://github.com/SmallNana/STSGCN_Pytorch) 
![Stars](https://img.shields.io/github/stars/SmallNana/STSGCN_Pytorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SmallNana/STSGCN_Pytorch?color=critical&style=social) | AAAI 2020

| Multivariable |  Traffic  
  Energy  
 NASDAQ  |      MLCNN       | [Towards Better Forecasting by Fusing Near and Distant Future Visions](https://ojs.aaai.org/index.php/AAAI/article/view/5466) |  [Pytorch](https://github.com/smallGum/MLCNN-Multivariate-Time-Series) 
![Stars](https://img.shields.io/github/stars/smallGum/MLCNN-Multivariate-Time-Series?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/smallGum/MLCNN-Multivariate-Time-Series?color=critical&style=social) | AAAI 2020

| Multivariable |  PEMS-S 
 PEMS-BAY 
 METR-LA  
 BJF 
 BRF 
 BRF-L |      SLCNN       | [Spatio-temporal graph structure learning for traffic forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/5770) | None | AAAI 2020

| Traffic Speed | METR-LA 
 PEMS-BAY  |        MRA-BGCN        | [Multi-Range Attentive Bicomponent Graph Convolutional Network for Traffic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/5758) | None | AAAI 2020

| Metro Flow | HKMetro |       WDGTC     | [Tensor Completion for Weakly-Dependent Data on Graph for Metro Passenger Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5915) |  [TF](https://github.com/bonaldli/WDG_TC)  
![Stars](https://img.shields.io/github/stars/bonaldli/WDG_TC?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/bonaldli/WDG_TC?color=critical&style=social) | AAAI 2020

| Multivariable | MovingMNIST 
 TaxiBJ 
  KTH |       SA-ConvLSTM     | [Self-Attention ConvLSTM for Spatiotemporal Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/6819) |  [TF](https://github.com/MahatmaSun1/SaConvSLTM) 
![Stars](https://img.shields.io/github/stars/MahatmaSun1/SaConvSLTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/MahatmaSun1/SaConvSLTM?color=critical&style=social) 
 [PyTorch](https://github.com/jerrywn121/TianChi_AIEarth)  | AAAI 2020

| Metro Flow | SydneyMetro  |      MLC-PPF    | [Potential Passenger Flow Prediction-A Novel Study for Urban Transportation Development](https://ojs.aaai.org/index.php/AAAI/article/view/5819) |  None | AAAI 2020

| Commuting Flow | Lodes 
 Pluto 
 OSRM  |     GMEL   | [Learning Geo-Contextual Embeddings for Commuting Flow Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5425) |  [Pytorch](https://github.com/jackmiemie/GMEL)  
![Stars](https://img.shields.io/github/stars/jackmiemie/GMEL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/jackmiemie/GMEL?color=critical&style=social) | AAAI 2020

| Multivariable | Traffic  
   Exchange  
 Solar   |       DeepTrends  | [Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/5496) | [TF](https://github.com/DerronXu/DeepTrends)    
![Stars](https://img.shields.io/github/stars/DerronXu/DeepTrends?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DerronXu/DeepTrends?color=critical&style=social) | AAAI 2020

| Multivariable | Traffic  
   Electricity   
 SmokeVideo   
 PCSales 
 RawMaterials  |       BHT  | [Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/6032) | [Python](https://github.com/huawei-noah/BHT-ARIMA)    
![Stars](https://img.shields.io/github/stars/huawei-noah/BHT-ARIMA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/huawei-noah/BHT-ARIMA?color=critical&style=social) | AAAI 2020

| Traffic Speed | PEMS04 
  PEMS07  
 PEMS08  |      LSGCN        | [LSGCN: Long Short-Term Traffic Prediction with Graph Convolutional Networks](https://dl.acm.org/doi/abs/10.5555/3491440.3491766) |  [TF](https://github.com/helanzhu/LSGCN) 
![Stars](https://img.shields.io/github/stars/helanzhu/LSGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/helanzhu/LSGCN?color=critical&style=social) | IJCAI 2020

| Traffic Flow  | BikeNYC 
 MobileBJ  |        CSCNet      | [A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling](https://dl.acm.org/doi/abs/10.5555/3491440.3491625) | None  | IJCAI 2020

| Multivariable | USDCNY  
   USDKRW   
 USDIDR   |       WATTNet  | [WATTNet: learning to trade FX via hierarchical spatio-temporal representation of highly multivariate time series](https://www.ijcai.org/proceedings/2020/0630.pdf) | [TF](https://github.com/pablovicente/keras-wattnet)    
![Stars](https://img.shields.io/github/stars/pablovicente/keras-wattnet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/pablovicente/keras-wattnet?color=critical&style=social) | IJCAI 2020

| Fine-grained | CitiBikeNYC 
  Div  
 Metro  |      GACNN        | [Towards Fine-grained Flow Forecasting: A Graph Attention Approach for Bike Sharing Systems](https://doi.org/10.1145/3366423.3380097) | None | WWW 2020

| Flow 
 Distribution | Austin 
  Louisville  
 Minneapolis  |      GCScoot        | [Dynamic Flow Distribution Prediction for Urban Dockless E-Scooter Sharing Reconfiguration](https://doi.org/10.1145/3366423.3380101) | None | WWW 2020

|  Traffic Speed | METR-LA 
 PEMS-BAY  |      STGNN        | [Traffic Flow Prediction via Spatial Temporal Graph Neural Network](https://doi.org/10.1145/3366423.3380186) |  [Pytorch](https://github.com/LMissher/STGNN)  
![Stars](https://img.shields.io/github/stars/LMissher/STGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LMissher/STGNN?color=critical&style=social) | WWW 2020

| Traffic Speed | DiDiCD  |      STAG-GCN        | [Spatiotemporal Adaptive Gated Graph Convolution Network for Urban Traffic Flow Forecasting](https://doi.org/10.1145/3340531.3411894) |  [Pytorch](https://github.com/RobinLu1209/STAG-GCN) 
![Stars](https://img.shields.io/github/stars/RobinLu1209/STAG-GCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/RobinLu1209/STAG-GCN?color=critical&style=social) | CIKM 2020

| Traffic Speed | METR-LA 
 PEMS-BAY   |     ST-GRAT       | [ST-GRAT: A Novel Spatio-temporal Graph Attention Networks for Accurately Forecasting Dynamically Changing Road Speed](https://doi.org/10.1145/3340531.3411940) |  [Pytorch](https://github.com/LMissher/ST-GRAT) 
![Stars](https://img.shields.io/github/stars/LMissher/ST-GRAT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LMissher/ST-GRAT?color=critical&style=social) | CIKM 2020

| Traffic Flow | BJ-Taxi 
  NYC-Taxi  
  NYC-Bike-1  
 NYC-Bike-2 |    ST-CGA      | [Spatial-Temporal Convolutional Graph Attention Networks for Citywide Traffic Flow Forecasting](https://doi.org/10.1145/3340531.3411941) |  [Keras](https://github.com/jbdj-star/cga) 
![Stars](https://img.shields.io/github/stars/jbdj-star/cga?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/jbdj-star/cga?color=critical&style=social) | CIKM 2020

| Traffic Flow | NYCBike  
   NYCTaxi    |       MT-ASTN  | [Multi-task Adversarial Spatial-Temporal Networks for Crowd Flow Prediction](https://doi.org/10.1145/3340531.3412054) | [Pytorch](https://github.com/MiaoHaoSunny/MT-ASTN)    
![Stars](https://img.shields.io/github/stars/MiaoHaoSunny/MT-ASTN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/MiaoHaoSunny/MT-ASTN?color=critical&style=social) | CIKM 2020

| Traffic Speed | SFO  
   NYC    |     DIGC  | [Deep Graph Convolutional Networks for Incident-Driven Traffic Speed Prediction](https://doi.org/10.1145/3340531.3411873) |  None   | CIKM 2020

| Metro Flow | SZMetro 
 HZMetro  |       STP-TrellisNets   | [STP-TrellisNets: Spatial-Temporal Parallel TrellisNets for Metro Station Passenger Flow Prediction](https://doi.org/10.1145/3340531.3411874) | None | CIKM 2020

| Multivariable | Air Quality  
  BikeNYC  
  METR-LA |   AGSTN   | [AGSTN: Learning Attention-adjusted Graph Spatio-Temporal Networks for Short-term Urban Sensor Value Forecasting](https://ieeexplore.ieee.org/abstract/document/9338255) |  [Keras](https://github.com/l852888/AGSTN) 
![Stars](https://img.shields.io/github/stars/l852888/AGSTN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/l852888/AGSTN?color=critical&style=social) | ICDM 2020

| Traffic Speed | METR-LA 
 PEMS-BAY  |   FreqST   | [FreqST: Exploiting Frequency Information in Spatiotemporal Modeling for Traffic Prediction](https://ieeexplore.ieee.org/abstract/document/9338305) |  None | ICDM 2020

| Traffic Flow | PEMS03 
  PEMS07 |   TSSRGCN   | [Tssrgcn: Temporal spectral spatial retrieval graph convolutional network for traffic flow forecasting](https://ieeexplore.ieee.org/abstract/document/9338393) |  None | ICDM 2020

| Multivariable | Air Quality  
   DarkSky 
    Geographic   |     DeepLATTE   | [Building Autocorrelation-Aware Representations for Fine-Scale Spatiotemporal Prediction](https://ieeexplore.ieee.org/abstract/document/9338402) | [Pytorch](https://github.com/spatial-computing/deeplatte-fine-scale-prediction)    
![Stars](https://img.shields.io/github/stars/spatial-computing/deeplatte-fine-scale-prediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/spatial-computing/deeplatte-fine-scale-prediction?color=critical&style=social) | ICDM 2020

| Traffic Flow  | XATaxi  
   BJTaxi 
    PortoTaxi   |     ST-PEFs   | [Interpretable Spatiotemporal Deep Learning Model for Traffic Flow Prediction Based on Potential Energy Fields](https://ieeexplore.ieee.org/abstract/document/9338315) | None  | ICDM 2020

| Traffic Speed 
 Flow   | SZSpeed  
   SZTaxi   |     cST-ML   | [cST-ML: Continuous Spatial-Temporal Meta-Learning for Traffic Dynamics Prediction](https://ieeexplore.ieee.org/abstract/document/9338315) | [Pytorch](https://github.com/yingxue-zhang/cST-ML)    
![Stars](https://img.shields.io/github/stars/yingxue-zhang/cST-ML?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yingxue-zhang/cST-ML?color=critical&style=social) | ICDM 2020

| Multivariable | Electricity 
 Traffic  
 Wiki 
 PEMS07(M) |         DeepGLO       | [Think Globally, Act Locally: A Deep Neural Network Approach to High-Dimensional Time Series Forecasting](https://proceedings.neurips.cc/paper/2019/hash/3a0844cee4fcf57de0c71e9ad3035478-Abstract.html) | [Pytorch](https://github.com/rajatsen91/deepglo) 
![Stars](https://img.shields.io/github/stars/rajatsen91/deepglo?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/rajatsen91/deepglo?color=critical&style=social) | NeurIPS 2019

| Multivariable | Electricity 
 Traffic  
 Solar 
 M4 
 Wind |         LogSparse       | [Enhancing the Locality and Breaking the Memory Bottleneck of Transformer on Time Series Forecasting](https://proceedings.neurips.cc/paper/2019/hash/6775a0635c302542da2c32aa19d86be0-Abstract.html) | [Pytorch](https://github.com/mlpotter/Transformer_Time_Series) 
![Stars](https://img.shields.io/github/stars/mlpotter/Transformer_Time_Series?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mlpotter/Transformer_Time_Series?color=critical&style=social) | NeurIPS 2019

| Multivariable  | Synthetic 
 ECG5000  
 Traffic  |        DILATE      | [Shape and Time Distortion Loss for Training Deep Time Series Forecasting Models](https://proceedings.neurips.cc/paper/2019/hash/466accbac9a66b805ba50e42ad715740-Abstract.html) | [Pytorch](https://github.com/vincent-leguen/DILATE)  
![Stars](https://img.shields.io/github/stars/vincent-leguen/DILATE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/vincent-leguen/DILATE?color=critical&style=social) | NeurIPS 2019

| Traffic Flow  | Earthquake  |        DeepUrbanEvent      | [DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events](https://doi.org/10.1145/3292500.3330996) | [Keras](https://github.com/deepkashiwa/DeepUrbanEvent)  
![Stars](https://img.shields.io/github/stars/deepkashiwa/DeepUrbanEvent?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/deepkashiwa/DeepUrbanEvent?color=critical&style=social) | KDD 2019

| Traffic Flow 
 Speed | TDrive 
  METR-LA   |         ST-MetaNet        | [Urban Traffic Prediction from Spatio-Temporal Data Using Deep Meta Learning](https://doi.org/10.1145/3292500.3330884) | [Mxnet](https://github.com/panzheyi/ST-MetaNet) 
![Stars](https://img.shields.io/github/stars/panzheyi/ST-MetaNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/panzheyi/ST-MetaNet?color=critical&style=social) | KDD 2019

| Multivariable  | Rossman  
 Walmart 
 Electricity 
 Traffic 
 Parts  |        ARU      | [Streaming Adaptation of Deep Forecasting Models using Adaptive Recurrent Units](https://doi.org/10.1145/3292500.3330996) | [TF](https://github.com/pratham16cse/ARU)  
![Stars](https://img.shields.io/github/stars/pratham16cse/ARU?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/pratham16cse/ARU?color=critical&style=social) | KDD 2019

| Multivariable  | Air Quality   |        AccuAir      | [AccuAir: Winning Solution to Air Quality Prediction for KDD Cup 2018](https://doi.org/10.1145/3292500.3330787) | None | KDD 2019

| Traffic Flow  | Simulated  
 RoadTraffic 
  Wikipedia |        ERMreg      | [Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions](https://doi.org/10.1145/3292500.3330976) | None | KDD 2019

| Multivariable 
 under event | Climate  
 Stock 
  Pseudo |        EVL      | [Modeling Extreme Events in Time Series Prediction](https://doi.org/10.1145/3292500.3330896) |None | KDD 2019

| Traffic Flow | PEMS04 
  PEMS08 
 METR-LA   |         ASTGCN        | [Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/3881) | [Mxnet](https://github.com/Davidham3/ASTGCN) 
![Stars](https://img.shields.io/github/stars/Davidham3/ASTGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Davidham3/ASTGCN?color=critical&style=social) | AAAI 2019

| Traffic Flow 
 Speed | NYC 
  PEMS0(M)  |         DGCNN        | [Dynamic spatial-temporal graph convolutional neural networks for traffic forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/3877) | None  | AAAI 2019

| Traffic FLow | NYC-Taxi 
  NYC-Bike  |        STDN      | [Revisiting Spatial-Temporal Similarity: A Deep Learning Framework for Traffic Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/4511) | [Keras](https://github.com/tangxianfeng/STDN)  
![Stars](https://img.shields.io/github/stars/tangxianfeng/STDN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tangxianfeng/STDN?color=critical&style=social) | AAAI 2019

| Traffic Flow   | MobileBJ  
 BikeNYC  |        DeepSTN+      | [DeepSTN+: context-aware spatial-temporal neural network for crowd flow prediction in metropolis](https://doi.org/10.1609/aaai.v33i01.33011020) | [TF](https://github.com/tsinghua-fib-lab/DeepSTN)  
![Stars](https://img.shields.io/github/stars/tsinghua-fib-lab/DeepSTN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tsinghua-fib-lab/DeepSTN?color=critical&style=social) | AAAI 2019

| Traffic Speed   | METR-LA  
  PEMS-BAY |       Res-RGNN    | [Gated residual recurrent graph neural networks for traffic prediction](https://doi.org/10.1609/aaai.v33i01.3301485) | None  | AAAI 2019

| Traffic FLow | MetroBJ  
  BusBJ  
 TaxiBJ |        GSTNet      | [GSTNet: Global Spatial-Temporal Network for Traffic Flow Prediction](https://www.ijcai.org/Proceedings/2019/0317.pdf) | [Pytorch](https://github.com/WoodSugar/GSTNet)  
![Stars](https://img.shields.io/github/stars/WoodSugar/GSTNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/WoodSugar/GSTNet?color=critical&style=social) | IJCAI 2019

| Traffic Speed  | METR-LA 
 PEMS-BAY  |        GWN      | [Graph WaveNet for Deep Spatial-Temporal Graph Modeling](https://doi.org/10.24963/ijcai.2019/264) | [Pytorch](https://github.com/nnzhan/Graph-WaveNet)  
![Stars](https://img.shields.io/github/stars/nnzhan/Graph-WaveNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nnzhan/Graph-WaveNet?color=critical&style=social) | IJCAI 2019

| Traffic Flow  | DidiSY 
 BikeNYC 
  TaxiBJ |        STG2Seq      | [STG2Seq: Spatial-Temporal Graph to Sequence Model for Multi-step Passenger Demand Forecasting](https://openreview.net/forum?id=Ein6fZbizNZ) | [TF](https://github.com/LeiBAI/STG2Seq)  
![Stars](https://img.shields.io/github/stars/LeiBAI/STG2Seq?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LeiBAI/STG2Seq?color=critical&style=social) | IJCAI 2019

| Multivariable | GHL 
  Electricity  
TEP |       DyAt   | [DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems](https://www.ijcai.org/Proceedings/2019/0441.pdf) | [Pytorch](https://github.com/nmuralid1/DynamicAttentionNetworks)  
![Stars](https://img.shields.io/github/stars/nmuralid1/DynamicAttentionNetworks?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nmuralid1/DynamicAttentionNetworks?color=critical&style=social) | IJCAI 2019

| Multivariable | Air Quality |       MGED   | [Multi-Group Encoder-Decoder Networks to Fuse Heterogeneous Data for Next-Day Air Quality Prediction](https://www.ijcai.org/proceedings/2019/0603.pdf) | None | IJCAI 2019

| Traffic Volumn  | Chicago 
 Boston  |        MetaST      | [Learning from Multiple Cities: A Meta-Learning Approach for Spatial-Temporal Prediction](https://doi.org/10.1145/3308558.3313577) | [TF](https://github.com/huaxiuyao/MetaST)  
![Stars](https://img.shields.io/github/stars/huaxiuyao/MetaST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/huaxiuyao/MetaST?color=critical&style=social) | WWW 2019

| TrafficPred 
 imputation |GZSpeed 
 HZMetro 
 Seattle 
 London |       BTF   | [Bayesian Temporal Factorization for Multidimensional Time Series Prediction](https://ieeexplore.ieee.org/abstract/document/9380704) | [Python](https://github.com/nmuralid1/DynamicAttentionNetworks)  
![Stars](https://img.shields.io/github/stars/nmuralid1/DynamicAttentionNetworks?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nmuralid1/DynamicAttentionNetworks?color=critical&style=social) | TPAMI 2019

| Multivariable | Gas Station |       DSANet   | [DSANet: Dual Self-Attention Network for Multivariate Time Series Forecasting](https://doi.org/10.1145/3357384.3358132) | [Pytorch](https://github.com/bighuang624/DSANet)  
![Stars](https://img.shields.io/github/stars/bighuang624/DSANet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/bighuang624/DSANet?color=critical&style=social) | CIKM 2019

| Multivariable | Solar 
 Traffic 
 Exchange 
 Electricity 
 PEMS ,etc |       Study   | [Experimental Study of Multivariate Time Series Forecasting Models](https://doi.org/10.1145/3357384.3357826) | None | CIKM 2019

| Traffic Speed | DiDiCD 
 DiDiXA  |   BTRAC   | [Boosted Trajectory Calibration for Traffic State Estimation](https://ieeexplore.ieee.org/abstract/document/8970880) | None  | ICDM 2019

| Multivariable | Photovoltaic  |       MTEX-CNN   | [MTEX-CNN: Multivariate Time Series EXplanations for Predictions with Convolutional Neural Networks](https://ieeexplore.ieee.org/abstract/document/8970899) | [Pytorch](https://github.com/duyanhpham-brs/XAI-Multivariate-Time-Series)  
![Stars](https://img.shields.io/github/stars/duyanhpham-brs/XAI-Multivariate-Time-Series?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/duyanhpham-brs/XAI-Multivariate-Time-Series?color=critical&style=social) | ICDM 2019

| Traffic Speed | BJER4 
 PEMS07(M)  
  PEMS07(L)  |        STGCN      | [Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting](https://openreview.net/forum?id=SkNeyVzOWB) | [TF](https://github.com/VeritasYin/STGCN_IJCAI-18) 
![Stars](https://img.shields.io/github/stars/VeritasYin/STGCN_IJCAI-18?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/VeritasYin/STGCN_IJCAI-18?color=critical&style=social) [Mxnet](https://github.com/Davidham3/STGCN)  [Pytorch1](https://github.com/FelixOpolka/STGCN-PyTorch)  
![Stars](https://img.shields.io/github/stars/FelixOpolka/STGCN-PyTorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/FelixOpolka/STGCN-PyTorch?color=critical&style=social) [Pytorch2](https://github.com/hazdzz/STGCN) [Pytorch3](https://github.com/Aguin/STGCN-PyTorch)   
![Stars](https://img.shields.io/github/stars/Aguin/STGCN-PyTorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Aguin/STGCN-PyTorch?color=critical&style=social) | IJCAI 2018

| Traffic Speed | METR-LA 
 PEMS-BAY  |      DCRNN  | [Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting](https://openreview.net/forum?id=SJiHXGWAZ) | [TF](https://github.com/liyaguang/DCRNN) 
![Stars](https://img.shields.io/github/stars/liyaguang/DCRNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liyaguang/DCRNN?color=critical&style=social) [Pytorch](https://github.com/chnsh/DCRNN_PyTorch)  |ICLR 2018

# [Multivariable Probabilistic Time Series Forecasting](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums:40+ |  |   |   |   |    |

| probability  | Exchange 
 ILI  
 ETT  
  Electricity 
  Traffic 
 Weather   |         TMDM      | [Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting](https://openreview.net/forum?id=qae04YACHs) | None  | ICLR 2024

| probability  | Exchange 
 Solar 
 Electricity 
  Traffic 
 Taxi 
  Wikipedia  |         VQ-TR       | [VQ-TR: Vector Quantized Attention for Time Series Forecasting](https://openreview.net/forum?id=IxpTsFS7mh) | None  | ICLR 2024

| Conformer |  COVID-19  |   CopulaCPTS     | [Copula Conformal prediction for multi-step time series prediction](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch54) | [Pytorch](hhttps://github.com/Rose-STL-Lab/CopulaCPTS)  
![Stars](https://img.shields.io/github/stars/Rose-STL-Lab/CopulaCPTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Rose-STL-Lab/CopulaCPTS?color=critical&style=social)  | ICLR 2024    

| probability  | Solar 
 Electricity 
  Traffic 
 Taxi 
 Wikipedia  |         LDT         | [ Latent Diffusion Transformer for Probabilistic Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/29085) | None  | AAAI 2024

| probability  | Solar 
 Electricity 
  Traffic 
 Exchange 
  M4-Hourly  
 UberTLC 
 KDDCup 
  Wikipedia  |         TSDiff         | [Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting](https://proceedings.neurips.cc/paper_files/paper/2023/hash/5a1a10c2c2c9b9af1514687bc24b8f3d-Abstract-Conference.html) | [GluonTS](https://github.com/amazon-science/unconditional-time-series-diffusion) 
![Stars](https://img.shields.io/github/stars/amazon-science/unconditional-time-series-diffusion?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/amazon-science/unconditional-time-series-diffusion?color=critical&style=social)  | NIPS 2023

| Quantile  |  Electricity 
 Kaggle 
  M4-daily 
  Traffic 
 Wiki   |         Ensemble        | [Theoretical Guarantees of Learning Ensembling Strategies with Applications to Time Series Forecasting](https://proceedings.mlr.press/v202/hasson23a.html) | None | ICML 2023

| Quantile  |  Boston 
 Concrete 
  kin8nm 
  Power 
 Protein  
 Wine  
 M5   |         BVAE        | [Neural Spline Search for Quantile Probabilistic Modeling](https://ojs.aaai.org/index.php/AAAI/article/view/26184) | None | AAAI 2023

| Quantile |  Traffc 
  Electricity 
 Solar Energy  |   pTSE     | [pTSE: A Multi-model Ensemble Method for Probabilistic Time Series Forecasting](https://www.ijcai.org/proceedings/2023/521) | None| IJCAI 2023   

| probability |  PEMS03 
  PEMS04 
 PEMS07  
 PEMS08   |   DeepSTUQ     | [Uncertainty Quantification for Traffic Forecasting: A Unified Approach](https://doi.org/10.1109/ICDE55515.2023.00081) | None| ICDE 2023  

| probability |  Electricity 
 Traffc 
  Solar 
  Exchange 
 M4 |   PDTrans     | [Probabilistic Decomposition Transformer for Time Series Forecasting](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch54) | [Pytorch](hhttps://github.com/JL-tong/PDTrans)  
![Stars](https://img.shields.io/github/stars/JL-tong/PDTrans?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JL-tong/PDTrans?color=critical&style=social)  | SDM 2023    

| probability |  Taxi
  
  Electricity  Traffc
 Exchange  |   COPDEEPAR     | [Coherent Probabilistic Forecasting of Temporal Hierarchies](https://proceedings.mlr.press/v206/rangapuram23a.html) | [GluonTS](https://github.com/awslabs/gluonts/tree/dev/src/gluonts/nursery/temporal_hierarchical_forecasting/model)  | AISTATS 2023     

| probability  |  Traffic 
 Electricity 
  Weather 
  ETT 
 Wind   |         BVAE        | [Generative Time Series Forecasting with Diffusion, Denoise, and Disentanglement](https://openreview.net/forum?id=rG0jm74xtx) | [Paddle](https://github.com/PaddlePaddle/PaddleSpatial/tree/main/research/D3VAE) | NeurIPS 2022

| probability & |   Stock Price  
  Wind Speed|         Volat        | [Volatility Based Kernels and Moving Average Means for Accurate Forecasting with Gaussian Processes](https://proceedings.mlr.press/v162/benton22a.html) |   [Pytorch,GPyTorch](https://github.com/g-benton/Volt)     
![Stars](https://img.shields.io/github/stars/g-benton/Volt?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/g-benton/Volt?color=critical&style=social) | ICML 2022

| probability & 
 Point & 
 Others |   electricity  
  Yacht 
 Boston, etc |         AQF        | [Autoregressive Quantile Flows for Predictive Uncertainty Estimation](https://openreview.net/forum?id=z1-I6rOKv1S) | None | ICLR 2022

| probability  | IRIS 
 Digits 
 EightSchools    |         EMF        | [Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling](https://openreview.net/forum?id=9pEJSVfDbba) | [Pytorch](https://github.com/gisilvs/EmbeddedModelFlows) 
![Stars](https://img.shields.io/github/stars/gisilvs/EmbeddedModelFlows?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gisilvs/EmbeddedModelFlows?color=critical&style=social) | ICLR 2022

| probability  | Bike Sharing 
 UCI 
 NYU Depth v2  |         NatPN        | [Natural Posterior Network: Deep Bayesian Predictive Uncertainty for Exponential Family Distributions](https://www.in.tum.de/daml/natpn/) | [Pytorch](https://github.com/borchero/natural-posterior-network) 
![Stars](https://img.shields.io/github/stars/borchero/natural-posterior-network?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/borchero/natural-posterior-network?color=critical&style=social) | ICLR 2022

| probability  | Carbon 
 Concrete 
 Energy 
 Housing,etc  |      β−NLL      | [On the Pitfalls of Heteroscedastic Uncertainty Estimation with Probabilistic Neural Networks](https://openreview.net/forum?id=aPOpXlnV1T) | [Pytorch](https://github.com/martius-lab/beta-nll) 
![Stars](https://img.shields.io/github/stars/martius-lab/beta-nll?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/martius-lab/beta-nll?color=critical&style=social) | ICLR 2022

| probability & Point | CDP 
 SLD |         STZINB-GNN        | [Uncertainty Quantification of Sparse Travel Demand Prediction with Spatial-Temporal Graph Neural Networks](https://doi.org/10.1145/3534678.3539093) | [Pytorch](https://github.com/ZhuangDingyi/STZINB) 
![Stars](https://img.shields.io/github/stars/ZhuangDingyi/STZINB?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ZhuangDingyi/STZINB?color=critical&style=social) | KDD 2022

| probability & Point | Sichuan 
 Panama |         PrEF        | [PrEF: Probabilistic Electricity Forecasting via Copula-Augmented State Space Model](https://aaai-2022.virtualchair.net/poster_aisi7128) | None | AAAI 2022

| probability | ETT 
 Solar 
 Electricity  |        KLST       | [Coherent Probabilistic Aggregate Queries on Long-horizon Forecasts](https://doi.org/10.24963/ijcai.2022/404) |  [Pytorch](https://github.com/pratham16cse/AggForecaster)  
![Stars](https://img.shields.io/github/stars/pratham16cse/AggForecaster?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/pratham16cse/AggForecaster?color=critical&style=social) | IJCAI 2022

| probability | Exchange 
 Solar 
  Electricity 
 Traffic 
 Wiki |        EMSSM       | [Memory Augmented State Space Model for Time Series Forecasting](https://doi.org/10.24963/ijcai.2022/479) |  None  | IJCAI 2022

| Prediction 
 Intervals | DMV 
  Census 
  Forest 
  Power |        Evaluation       | [Prediction Intervals for Learned Cardinality Estimation: An Experimental Evaluation](https://doi.org/10.24963/ijcai.2022/404) |  None | ICDE 2022

| Periodic Forecasting |  ETT 
 Weather   |      DeepFS   | [Bridging Self-Attention and Time Series Decomposition for Periodic Forecasting](https://doi.org/10.1145/3511808.3557077) | None | CIKM 2022

| probability  | Electricity 
 Traffic 
 Wiki  
 M4   |     ISQF     | [Learning Quantile Functions without Quantile Crossing for Distribution-free Time Series Forecasting](https://proceedings.mlr.press/v151/park22a.html) | [GluonTS](https://github.com/awslabs/gluonts/blob/4fef7e26470d15096b11b005be846dedf87fb736/src/gluonts/torch/distributions/isqf.py) | AISTATS 2022

| probability  |  M4 
 Traffic 
  Electricity    |     Robust     | [Robust Probabilistic Time Series Forecasting](https://arxiv.org/abs/2202.11910) | [GluonTS](https://github.com/tetrzim/robust-probabilistic-forecasting)  | AISTATS 2022

| probability  | Electricity  
 Traffic 
 M4     |     MQF     | [Multivariate Quantile Function Forecaster](https://arxiv.org/pdf/2202.11316.pdf) | [GluonTS](https://github.com/awslabs/gluon-ts/tree/master/src/GluonTS/torch/model/mqf2)  | AISTATS 2022

| probability  |  Electricity 
 Traffic 
  Wiki 
  Azure |         C2FAR        | [C2FAR: Coarse-to-Fine Autoregressive Networks for Precise Probabilistic Forecasting](https://openreview.net/forum?id=lHuPdoHBxbg) | [Future](https://github.com/huaweicloud/c2far_forecasting) | AISTATS 2022

| Imputation & 
 Probabilistic | PhysioNet  
 Air Quality  |         CSDI       | [CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation](https://proceedings.neurips.cc/paper/2021/hash/cfe8504bda37b575c70ee1a8276f3486-Abstract.html) | [Pytorch](https://github.com/ermongroup/CSDI) 
![Stars](https://img.shields.io/github/stars/ermongroup/CSDI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ermongroup/CSDI?color=critical&style=social) | NeurIPS 2021

| probability | MIMIC-III 
 EEG 
 COVID-19  |        CF-RNN      | [Conformal Time-series Forecasting](https://proceedings.neurips.cc/paper/2021/hash/312f1ba2a72318edaaa995a67835fad5-Abstract.html) |  [Pytorch](https://github.com/kamilest/conformal-rnn) 
![Stars](https://img.shields.io/github/stars/kamilest/conformal-rnn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/kamilest/conformal-rnn?color=critical&style=social) | NeurIPS 2021

| probability | CDC Flu  |       EPIFNP     | [When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting](https://proceedings.neurips.cc/paper/2021/hash/a4a1108bbcc329a70efa93d7bf060914-Abstract.html) |  [Pytorch](https://github.com/AdityaLab/EpiFNP) 
![Stars](https://img.shields.io/github/stars/AdityaLab/EpiFNP?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AdityaLab/EpiFNP?color=critical&style=social) | NeurIPS 2021

| probability | Basketball  
  Weather|       GLIM     | [Probability Paths and the Structure of Predictions over Time](https://proceedings.neurips.cc/paper/2021/hash/7f53f8c6c730af6aeb52e66eb74d8507-Abstract.html) |   [R](https://github.com/ItsMrLin/probability-paths) | NeurIPS 2021

| probability | Facebook  
  Meps 
 Star 
 Bike ,etc |       LSF     | [Probabilistic Forecasting: A Level-Set Approach](https://proceedings.neurips.cc/paper/2021/hash/32b127307a606effdcc8e51f60a45922-Abstract.html) |   [GluonTS](https://github.com/awslabs/gluon-ts/tree/master/src/GluonTS/model/rotbaum) | NeurIPS 2021

| probability | Solar  
  Electricity 
 Traffic  
 Taxi 
 Wikipedia |       ProTran     | [Probabilistic Transformer For Time Series Analysis](https://proceedings.neurips.cc/paper/2021/hash/c68bd9055776bf38d8fc43c0ed283678-Abstract.html) |   None | NeurIPS 2021

| Prediction 
 Intervals | Solar 
 Wind   |        EnbPI      | [Conformal prediction interval for dynamic time-series](http://proceedings.mlr.press/v139/xu21h.html) |  [Pytorch](https://github.com/hamrel-cxu/EnbPI) 
![Stars](https://img.shields.io/github/stars/hamrel-cxu/EnbPI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hamrel-cxu/EnbPI?color=critical&style=social) | ICML 2021

| probability | Exchange 
 Solar 
 Electricity 
 Traffic 
  Taxi  
   Wiki  |        TimeGrad      | [Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting](http://proceedings.mlr.press/v139/rasul21a.html) |  [Pytorch](https://github.com/zalandoresearch/pytorch-ts) 
![Stars](https://img.shields.io/github/stars/zalandoresearch/pytorch-ts?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zalandoresearch/pytorch-ts?color=critical&style=social) | ICML 2021

| probability & Point | PEMS03 
 PEMS04 
 PEMS07 
 PEMS08 
  Electricity  
   Traffic , etc |         AGCGRU        | [RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting](https://proceedings.mlr.press/v139/pal21b.html) |  [TF](https://github.com/networkslab/rnn_flow) 
![Stars](https://img.shields.io/github/stars/networkslab/rnn_flow?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/networkslab/rnn_flow?color=critical&style=social) | ICML 2021

| probability | Tourism 
 Labour 
 Traffic 
 Wiki 
  Electricity  
   Traffic , etc |         Hier-E2E        | [End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series](http://proceedings.mlr.press/v139/rangapuram21a.html) |  [MXNet](https://github.com/rshyamsundar/GluonTS-hierarchical-ICML-2021) | ICML 2021

| probability | Sine 
 MNIST 
 Billiards 
 S&P 
  Stock   |        Whittle      | [Whittle Networks: A Deep Likelihood Model for Time Series](http://proceedings.mlr.press/v139/yu21c.html) | [TF](https://github.com/ml-research/WhittleNetworks) 
![Stars](https://img.shields.io/github/stars/ml-research/WhittleNetworks?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ml-research/WhittleNetworks?color=critical&style=social) | ICML 2021

| probability | METR-LA 
 PEMS-BAY 
 PMU   |        GTS      | [Discrete Graph Structure Learning for Forecasting Multiple Time Series](https://openreview.net/forum?id=WEHSlH5mOk) | [Pytorch](https://github.com/chaoshangcs/GTS) 
![Stars](https://img.shields.io/github/stars/chaoshangcs/GTS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chaoshangcs/GTS?color=critical&style=social) | ICLR 2021

| probability & Point| Exchange 
Solar 
 Electricity 
 Traffic 
 Taxi  
 Wikipedia |        MAF      | [Multivariate Probabilistic Time Series Forecasting via Conditioned Normalizing Flows](https://openreview.net/forum?id=WiGQBFuVRv) | [Pytorch](https://github.com/zalandoresearch/pytorch-ts) 
![Stars](https://img.shields.io/github/stars/zalandoresearch/pytorch-ts?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zalandoresearch/pytorch-ts?color=critical&style=social) | ICLR 2021

| probability | MNIST 
 PhysioNet2012  |        PNCNN      | [Probabilistic Numeric Convolutional Neural Networks](https://openreview.net/forum?id=T1XmO8ScKim) | None  | ICLR 2021

| probability & Point | Energy 
 Wine 
 Power 
 MSD, etc |         PGBM        | [Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression](https://dl.acm.org/doi/10.1145/3447548.3467278) |  [Pytorch](https://github.com/elephaint/pgbm) 
![Stars](https://img.shields.io/github/stars/elephaint/pgbm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/elephaint/pgbm?color=critical&style=social) | KDD 2021

| probability | DiDICD   |        TrajNet      | [TrajNet: A Trajectory-Based Deep Learning Model for Traffic Prediction](https://doi.org/10.1145/3447548.3467236) | None | KDD 2021

| probability | Air Quality  
  METR-LA 
  COVID-19  |        UQ      | [Quantifying Uncertainty in Deep Spatiotemporal Forecasting](https://doi.org/10.1145/3447548.3467325) | [Pytorch](https://github.com/DongxiaW/Quantifying_Uncertainty_in_Deep_Spatiotemporal_Forecasting) 
![Stars](https://img.shields.io/github/stars/DongxiaW/Quantifying_Uncertainty_in_Deep_Spatiotemporal_Forecasting?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DongxiaW/Quantifying_Uncertainty_in_Deep_Spatiotemporal_Forecasting?color=critical&style=social) | KDD 2021

| probability  | Electricity 
 Traffic 
 Environment 
 Air Quality 
 Dewpoint,etc|        VSMHN      | [Synergetic Learning of Heterogeneous Temporal Sequences for Multi-Horizon Probabilistic Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/17023) | [Pytorch](https://github.com/longyuanli/VSMHN) 
![Stars](https://img.shields.io/github/stars/longyuanli/VSMHN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/longyuanli/VSMHN?color=critical&style=social) | AAAI 2021

| probability & Point | Traffic 
 Electricity 
 Wiki 
 Solar 
 Taxi |        TLAE      | [Temporal Latent Auto-Encoder: A Method for Probabilistic Multivariate Time Series Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/17101) | None | AAAI 2021

| probability  | Patient EHR 
 Public Health |        UNITE      | [UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data](https://doi.org/10.1145/3442381.3450087) | [Pytorch](https://github.com/Chacha-Chen/UNITE) 
![Stars](https://img.shields.io/github/stars/Chacha-Chen/UNITE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Chacha-Chen/UNITE?color=critical&style=social) | WWW 2021

| probability  | Exchange 
 Solar 
 Electricity  
 Traffic  
  Wiki  |     ARSGLS     | [Deep Rao-Blackwellised Particle Filters for Time Series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/afb0b97df87090596ae7c503f60bb23f-Abstract.html) | None | NeurIPS 2020

| probability  | Electricity 
 Traffic 
 Wind  
 Solar  
  M4  |     AST     | [Adversarial Sparse Transformer for Time Series Forecasting](https://proceedings.neurips.cc/paper/2020/hash/c6b8c8d762da15fa8dbbdfb6baf9e260-Abstract.html) | [Pytorch](https://github.com/hihihihiwsf/AST)  
![Stars](https://img.shields.io/github/stars/hihihihiwsf/AST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hihihihiwsf/AST?color=critical&style=social) | NeurIPS 2020

| probability  | Traffic 
 Electricity   |     STRIPE     | [Probabilistic Time Series Forecasting with Shape and Temporal Diversity](https://papers.NeurIPS.cc/paper/2020/hash/2f2b265625d76a6704b08093c652fd79-Abstract.html) | [Pytorch](https://github.com/vincent-leguen/STRIPE)  
![Stars](https://img.shields.io/github/stars/vincent-leguen/STRIPE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/vincent-leguen/STRIPE?color=critical&style=social) | NeurIPS 2020

| probability  | Exchange 
 Solar 
 Electricity  
 Wiki  
  Traffic  |     NKF     | [Normalizing Kalman Filters for Multivariate Time Series Analysis](https://proceedings.neurips.cc/paper/2020/hash/1f47cef5e38c952f94c5d61726027439-Abstract.html) |  None  | NeurIPS 2020

| quantile  |  MIMIC-III |    BJRNN    | [Frequentist Uncertainty in RNNs via Blockwise Influence Functions](http://proceedings.mlr.press/v119/alaa20b.html) | [Pytorch](https://github.com/ahmedmalaa/rnn-blockwise-jackknife)  
![Stars](https://img.shields.io/github/stars/ahmedmalaa/rnn-blockwise-jackknife?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ahmedmalaa/rnn-blockwise-jackknife?color=critical&style=social) | ICML 2020

| probability  |  S&P 500 
 Electricity   |     Monte-Carlo     | [Adversarial Attacks on Probabilistic Autoregressive Forecasting Models](https://proceedings.mlr.press/v119/dang-nhu20a.html) | [Pytorch](https://github.com/eth-sri/probabilistic-forecasts-attacks)  
![Stars](https://img.shields.io/github/stars/eth-sri/probabilistic-forecasts-attacks?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/eth-sri/probabilistic-forecasts-attacks?color=critical&style=social) | ICML 2020

| probability  |  Boston 
 Concrete  
Energy 
 Kin8nm 
  Naval, etc  |    NGBoost    | [NGBoost: Natural Gradient Boosting for Probabilistic Prediction](http://proceedings.mlr.press/v119/duan20a.html) | [Python](https://github.com/stanfordmlgroup/ngboost)  
![Stars](https://img.shields.io/github/stars/stanfordmlgroup/ngboost?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/stanfordmlgroup/ngboost?color=critical&style=social) | ICML 2020

| probability  |  Physionet 
 NHIS   |    DME    | [Deep Mixed Effect Model Using Gaussian Processes: A Personalized and Reliable Prediction for Healthcare](https://ojs.aaai.org/index.php/AAAI/article/view/5773) | [Pytorch](https://github.com/jik0730/Deep-Mixed-Effect-Model-using-Gaussian-Processes)  
![Stars](https://img.shields.io/github/stars/jik0730/Deep-Mixed-Effect-Model-using-Gaussian-Processes?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/jik0730/Deep-Mixed-Effect-Model-using-Gaussian-Processes?color=critical&style=social) | AAAI 2020

| probability  |  Exchange 
 Solar 
  Electricity  
  Traffic  
  NYCTaxi 
 Wikipedia  |    copula    | [High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes](https://proceedings.neurips.cc/paper/2019/hash/0b105cf1504c4e241fcc6d519ea962fb-Abstract.html) | [GluonTS](https://github.com/mbohlkeschneider/gluon-ts/tree/mv_release)  | NeurIPS 2019

| probability  |  Electricity 
 Traffic 
  NYCTaxi  
  Uber   |    DF    | [Deep Factors for Forecasting](https://proceedings.mlr.press/v97/wang19k.html) | None | ICML 2019

| probability  |  Weather   |    DUQ    | [Deep Uncertainty Quantification: A Machine Learning Approach for Weather Forecasting](https://doi.org/10.1145/3292500.3330704) | [Keras](https://github.com/BruceBinBoxing/Deep_Learning_Weather_Forecasting)  
![Stars](https://img.shields.io/github/stars/BruceBinBoxing/Deep_Learning_Weather_Forecasting?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BruceBinBoxing/Deep_Learning_Weather_Forecasting?color=critical&style=social) | KDD 2019

| probability  |  JD50K   |    framework    | [Multi-Horizon Time Series Forecasting with Temporal Attention Learning](https://doi.org/10.1145/3292500.3330662) | None  | KDD 2019

| probability  |  MIMIC-III   |    TPF    | [Temporal Probabilistic Profiles for Sepsis Prediction in the ICU](https://doi.org/10.1145/3292500.3330747) | None  | KDD 2019

| probability  | Electricity 
 Traffic 
  Wiki  
  Dom    |    SQF    | [Probabilistic Forecasting with Spline Quantile Function RNNs](https://proceedings.mlr.press/v89/gasthaus19a.html) | None  | AISTATS 2019

| probability  | More |         More        | [https://github.com/zzw-zwzhang/Awesome-of-Time-Series-Prediction](https://github.com/zzw-zwzhang/Awesome-of-Time-Series-Prediction) |  More |  

# [Time Series Imputation](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums: 30+  |  |   |   |   |    |

| ImputeFormer | METR-LA   
 PEMS-BAY  
  PEMS03478  
  Solar 
 CER-EN 
  AQI  |         ImputeFormer        | [ImputeFormer: Low Rankness-Induced Transformers for Generalizable Spatiotemporal Imputation](https://dl.acm.org/doi/abs/10.1145/3637528.3671751) | [Pytorch](https://github.com/tongnie/ImputeFormer) 
![Stars](https://img.shields.io/github/stars/tongnie/ImputeFormer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tongnie/ImputeFormer?color=critical&style=social)  | KDD 2024

| Imputation | AirQuality   
 Stocks  
  Electricity  
  Energy  |         CTA        | [Continuous-time Autoencoders for Regular and Irregular Time Series Imputation](https://proceedings.mlr.press/v202/chen23f.html) | [Pytorch](https://github.com/hyowonwi/CTA) 
![Stars](https://img.shields.io/github/stars/hyowonwi/CTA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hyowonwi/CTA?color=critical&style=social)  | WSDM 2024

| Imputation | PM2.5 
 PhysioNet |         CSBI        | [Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation](https://proceedings.mlr.press/v202/chen23f.html) | [Pytorch](https://github.com/morganstanley/MSML) 
![Stars](https://img.shields.io/github/stars/morganstanley/MSML?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/morganstanley/MSML?color=critical&style=social)  | ICML 2023

| Imputation | MIMIC-III 
 PhysioNet |         MNAR        | [Probabilistic Imputation for Time-series Classification with Missing Data](https://proceedings.mlr.press/v202/kim23m.html) | [TF](https://github.com/yuneg11/SupNotMIWAE-with-ObsDropout) 
![Stars](https://img.shields.io/github/stars/yuneg11/SupNotMIWAE-with-ObsDropout?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yuneg11/SupNotMIWAE-with-ObsDropout?color=critical&style=social)  | ICML 2023

| Imputation | Guangzhou 
 Solar-energy
 Westminster |         TIDER 
(EncDec,AR)        | [Multivariate Time-series Imputation with Disentangled Temporal Representations](https://openreview.net/forum?id=rdjeCNUS6TG) |  [Pytorch](https://anonymous.4open.science/r/TIDER-527C/readme.md) | ICLR 2023

| Imputation | COVID-19   
 AQ36   
 PeMS-BA 
 PeMS-LA 
 PeMS-SD|       PoGeVon     | [Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders](https://dl.acm.org/doi/abs/10.1145/3580305.3599444) |  [Author](https://github.com/Derek-Wds) | KDD 2023

| Imputation | PhysioNet   
 Human Activity |       Warpformer     | [Warpformer: A Multi-scale Modeling Approach for Irregular Clinical Time Series](https://dl.acm.org/doi/10.1145/3580305.3599543) |  [Pytorch](https://github.com/imJiawen/Warpformer) 
![Stars](https://img.shields.io/github/stars/imJiawen/Warpformer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/imJiawen/Warpformer?color=critical&style=social)  | KDD 2023

| Imputation | Air Quality 
 METR-LA
 PEMS-BAY |         PriSTI        | [PriSTI: A Conditional Diffusion Framework for Spatiotemporal Imputation](https://arxiv.org/abs/2302.09746) |  [Pytorch](https://github.com/LMZZML/PriSTI) 
![Stars](https://img.shields.io/github/stars/LMZZML/PriSTI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LMZZML/PriSTI?color=critical&style=social)  | ICDE 2023

| Imputation | PhysioNet12 
 PhysioNet19 
 MIMIC-III |       DA-TASWDM     | [Density-Aware Temporal Attentive Step-wise Diffusion Model For Medical Time Series Imputation](https://dl.acm.org/doi/10.1145/3583780.3614840) |  None | CIKM 2023

| Imputation | TEDDY  
 CAMELS |         TSEst        | [Attention-Based Multi-modal Missing Value Imputation for Time Series Data with High Missing Rate](hhttps://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch53) |  [Pytorch](https://github.com/compbiolabucf/TSEst) 
![Stars](https://img.shields.io/github/stars/compbiolabucf/TSEst?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/compbiolabucf/TSEst?color=critical&style=social)  | SDM 2023

| Imputation |  Air Quality 
 METR-LA 
 PEMS-BAY 
 CER-E  |         GRIN 
(EncDec,AR)        | [Filling the G_ap_s-Multivariate Time Series Imputation by Graph Neural Networks](https://openreview.net/forum?id=kOu3-S3wJ7) |  [Pytorch](https://github.com/Graph-Machine-Learning-Group/grin) 
![Stars](https://img.shields.io/github/stars/Graph-Machine-Learning-Group/grin?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Graph-Machine-Learning-Group/grin?color=critical&style=social) | ICLR 2022

| Imputation |  PhysioNet 
 MIMIC-III 
 Climate  |         HeTVAE  
(Attn,VAE)        | [Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series](https://openreview.net/forum?id=Az7opqbQE-3) |  [Pytorch](https://github.com/reml-lab/hetvae) 
![Stars](https://img.shields.io/github/stars/reml-lab/hetvae?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/reml-lab/hetvae?color=critical&style=social) | ICLR 2022

| Imputation |  MIMIC-III 
 OPHTHALMIC 
 MNIST Physionet 
 |         GIL   
(AR,Attn, 
 GRADIENT LEARNING)          | [Gradient Importance Learning for Incomplete Observations](https://openreview.net/forum?id=fXHl76nO2AZ) |  [TF](https://github.com/gaoqitong/gradient-importance-learning) 
![Stars](https://img.shields.io/github/stars/gaoqitong/gradient-importance-learning?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gaoqitong/gradient-importance-learning?color=critical&style=social) | ICLR 2022

| Imputation | Chlorine level 
 SML2010 
 Air Quality |         D-NLMC        | [Dynamic Nonlinear Matrix Completion for Time-Varying Data Imputation](https://aaai-2022.virtualchair.net/poster_aaai12088) | [Matlab](https://github.com/jicongfan) 
 Author 
 Github | AAAI 2022

| Imputation | COMPAS 
 Adult 
 HSLS |         ME        | [Online Missing Value Imputation and Change Point Detection with the Gaussian Copula](https://aaai-2022.virtualchair.net/poster_aaai6237) | [gcimpute](https://github.com/yuxuanzhao2295/Online-Missing-Value-Imputation-and-Change-Point-Detection-with-the-Gaussian-Copula) | AAAI 2022

| Imputation |       Fair MIP Forest   |       | [Fairness without Imputation: A Decision Tree Approach for Fair Prediction with Missing Values](https://ojs.aaai.org/index.php/AAAI/article/view/21189) | None | AAAI 2022

| Imputation |  Chengdu 
 New York   |      STCPA   | [Traffic Speed Imputation with Spatio-Temporal Attentions and Cycle-Perceptual Training](https://doi.org/10.1145/3511808.3557480) | [Pytorch](https://github.com/Sam1224/STCPA) 
![Stars](https://img.shields.io/github/stars/Sam1224/STCPA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Sam1224/STCPA?color=critical&style=social) | CIKM 2022

| Imputation |   Nanjingyby 
  PEMS08   |   AST-CMCN  | [Generative-Free Urban Flow Imputation](https://doi.org/10.1145/3511808.3557334) | SenzhangWang | CIKM 2022

| Imputation |   Foursquare 
  Gowalla   |   MDI-MG  | [Multi-task Generative Adversarial Network for Missing Mobility Data Imputation](https://doi.org/10.1145/3511808.3557654) | None | CIKM 2022

| Imputation |   Self-defined   |  MACRO  | [Multi-Graph Convolutional Recurrent Network for Fine-Grained Lane-Level Traffic Flow Imputation](https://ieeexplore.ieee.org/document/10027759) | [Pytorch](https://github.com/Jingci/MACRO) 
![Stars](https://img.shields.io/github/stars/Jingci/MACRO?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Jingci/MACRO?color=critical&style=social) | ICDM 2022

| Imputation | Physionet 
 MIMIC-III 
 Human Activity  |         mTAND        | [Multi-Time Attention Networks for Irregularly Sampled Time Series](https://openreview.net/forum?id=4c0J6lwQ4_) | [Pytorch](https://github.com/reml-lab/mTAN)  
![Stars](https://img.shields.io/github/stars/reml-lab/mTAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/reml-lab/mTAN?color=critical&style=social) | ICLR 2021

| Imputation | METR-LA 
 NREL 
 USHCN 
 SeData |         IGNNK        | [Inductive Graph Neural Networks for Spatiotemporal Kriging](https://ojs.aaai.org/index.php/AAAI/article/view/16575) | [Pytorch](https://github.com/Kaimaoge/IGNNK) 
![Stars](https://img.shields.io/github/stars/Kaimaoge/IGNNK?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Kaimaoge/IGNNK?color=critical&style=social) | AAAI 2021

| Imputation | Activity  
 PhysioNet 
 Air Quality |         SSGAN       | [Generative Semi-supervised Learning for Multivariate Time Series Imputation](https://ojs.aaai.org/index.php/AAAI/article/view/17086) | [Pytorch](https://github.com/zjuwuyy-DL/Generative-Semi-supervised-Learning-for-Multivariate-Time-Series-Imputation) 
![Stars](https://img.shields.io/github/stars/zjuwuyy-DL/Generative-Semi-supervised-Learning-for-Multivariate-Time-Series-Imputation?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zjuwuyy-DL/Generative-Semi-supervised-Learning-for-Multivariate-Time-Series-Imputation?color=critical&style=social) | AAAI 2021

| Imputation & 
 Multivariable | PhysioNet  
 Air Quality  |         CSDI       | [CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation](https://proceedings.neurips.cc/paper/2021/hash/cfe8504bda37b575c70ee1a8276f3486-Abstract.html) | [Pytorch](https://github.com/ermongroup/CSDI) 
![Stars](https://img.shields.io/github/stars/ermongroup/CSDI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ermongroup/CSDI?color=critical&style=social) | NeurIPS 2021

| Imputation & 
 Prediction  | VevoMusic  
 WikiTraffic 
 Los-Loop 
 SZ-Taxi |         Radflow       | [Radflow: A Recurrent, Aggregated, and Decomposable Model for Networks of Time Series](https://dl.acm.org/doi/10.1145/3442381.3449945) | [Pytorch](https://github.com/alasdairtran/radflow) 
![Stars](https://img.shields.io/github/stars/alasdairtran/radflow?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/alasdairtran/radflow?color=critical&style=social) | WWW 2021

| Imputation | PhysioNet  
 Air Quality 
 Gas Sensor |         STING       | [STING: Self-attention based Time-series Imputation Networks using GAN](https://ieeexplore.ieee.org/abstract/document/9679183) | None | ICDM 2021

| Imputation  | Zero 
 MICE 
  SoftImpute  
  GMMC 
 GAIN   |    SN    | [Why Not to Use Zero Imputation? Correcting Sparsity Bias in Training Neural Networks](https://openreview.net/forum?id=BylsKkHYvH) | [Future](https://github.com/JoonyoungYi/sparsity-normalization)  | ICLR 2020

| Imputation  | Beijing Air 
 PhysioNet 
  Porto Taxi 
  London Weather  |   LGnet   | [Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values](https://ojs.aaai.org/index.php/AAAI/article/view/6056) | None | AAAI 2020

| Imputation  | Sydney 
 Melbourne 
  Brisbane 
  Perth, etc   |    SMV-NMF    | [A spatial missing value imputation method for multi-view urban statistical data](https://www.ijcai.org/Proceedings/2020/0182.pdf) | [Matlab](https://github.com/SMV-NMF/SMV-NMF)  | IJCAI 2020

| Imputation  | PhysioNet 
 Air Quality 
  Wind  |   GANGRUI   | [Adversarial Recurrent Time Series Imputation](https://ieeexplore.ieee.org/abstract/document/9158560/) | None | TNNLS 2020

| Imputation  | Healthcare 
 Climate  |   GRU-ODE-Bayes   | [GRU-ODE-Bayes: Continuous Modeling of Sporadically-Observed Time Series](https://proceedings.neurips.cc/paper/2019/hash/455cb2657aaa59e32fad80cb0b65b9dc-Abstract.html) | [Pytorch](https://github.com/edebrouwer/gru_ode_bayes) 
![Stars](https://img.shields.io/github/stars/edebrouwer/gru_ode_bayes?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/edebrouwer/gru_ode_bayes?color=critical&style=social) | NeurIPS 2019

| Imputation  |  Toy |   LatenODE   | [Latent Ordinary Differential Equations for Irregularly-Sampled Time Series](https://proceedings.neurips.cc/paper/2019/hash/42a6845a557bef704ad8ac9cb4461d43-Abstract.html) | [Pytorch](https://github.com/YuliaRubanova/latent_ode) 
![Stars](https://img.shields.io/github/stars/YuliaRubanova/latent_ode?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YuliaRubanova/latent_ode?color=critical&style=social) | NeurIPS 2019

| Imputation  |  Sines 
  Stocks
 Energy 
 Events |   TimeGAN   | [Time-series Generative Adversarial Networks](https://proceedings.neurips.cc/paper/2019/hash/c9efe5f26cd17ba6216bbe2a7d26d490-Abstract.html) | [TF](https://github.com/jsyoon0823/TimeGAN) 
![Stars](https://img.shields.io/github/stars/jsyoon0823/TimeGAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/jsyoon0823/TimeGAN?color=critical&style=social) | NeurIPS 2019

| Imputation  |  MIMIC-III  
  UWaveGesture  |   Inter-net   | [Interpolation-Prediction Networks for Irregularly Sampled Time Series](https://openreview.net/forum?id=r1efr3C9Ym) | [Keras](https://github.com/mlds-lab/interp-net) 
![Stars](https://img.shields.io/github/stars/mlds-lab/interp-net?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mlds-lab/interp-net?color=critical&style=social) | ICLR 2019

| Imputation  | PhysioNet  
  KDD2018  |  E2gan   | [E2gan: End-to-end generative adversarial network for multivariate time series imputation](https://www.ijcai.org/Proceedings/2019/0429.pdf) | [TF](https://github.com/Luoyonghong/E2EGAN) 
![Stars](https://img.shields.io/github/stars/Luoyonghong/E2EGAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Luoyonghong/E2EGAN?color=critical&style=social) | IJCAI 2019

| Imputation  | EC  
  RV  |  STI   | [How Do Your Neighbors Disclose Your Information: Social-Aware Time Series Imputation](https://doi.org/10.1145/3308558.3313714) | [Pytorch](https://github.com/tomstream/STI) 
![Stars](https://img.shields.io/github/stars/tomstream/STI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tomstream/STI?color=critical&style=social) | WWW 2019

# [Time Series Anomaly Detection](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums: 30+  |  |      |     |     |   |

|  Anomaly Detection | Yahoo 
 KPI 
 WSD 
  NAB   |       FCVAE   | [Revisiting VAE for Unsupervised Time Series Anomaly Detection: A Frequency Perspective](https://dl.acm.org/doi/abs/10.1145/3589334.3645710) |  [Pytorch](https://github.com/CSTCloudOps/FCVAE) 
![Stars](https://img.shields.io/github/stars/CSTCloudOps/FCVAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CSTCloudOps/FCVAE?color=critical&style=social)  | WWW 2024

|  Anomaly Detection | TODS 
 ASD
 ECG 
PSM 
 CompanyA |       Dual-TF    | [Breaking the Time-Frequency Granularity Discrepancy in Time-Series Anomaly Detection](https://dl.acm.org/doi/10.1145/3589334.3645556) |  [Pytorch](https://github.com/kaist-dmlab/DualTF) 
![Stars](https://img.shields.io/github/stars/kaist-dmlab/DualTF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/kaist-dmlab/DualTF?color=critical&style=social)  | WWW 2024

|  Anomaly Detection | SMD 
 J-D1 
 J-D2 
SMAP |       LARA    | [LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection](https://dl.acm.org/doi/10.1145/3589334.3645472) | None  | WWW 2024

|  Anomaly Detection | SWaT 
  WADI 
  PSM 
  SMD 
 MSL  
 SMAP  
  Crediy 
 Yahoo |           | [When Model Meets New Normals: Test-Time Adaptation for Unsupervised Time-Series Anomaly Detection](https://ojs.aaai.org/index.php/AAAI/article/view/29210) | [Pytorch](https://github.com/ForestsKing/D3R) 
![Stars](https://img.shields.io/github/stars/ForestsKing/D3R?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ForestsKing/D3R?color=critical&style=social) | AAAI 2024

|  Anomaly Detection | SMD 
 MSL 
 SMAP 
 SWaT 
 PSM  |   MEMTO        | [MEMTO: Memory-guided Transformer for Multivariate Time Series Anomaly Detection](https://proceedings.neurips.cc/paper_files/paper/2023/hash/b4c898eb1fb556b8d871fbe9ead92256-Abstract-Conference.html) | No | NIPS 2023

|  Anomaly Detection | PSM 
 SMD 
 SWaT |   D3R        | [Drift doesn’t Matter: Dynamic Decomposition with Diffusion Reconstruction for Unstable Multivariate Time Series Anomaly Detection](https://proceedings.neurips.cc/paper_files/paper/2023/hash/22f5d8e689d2a011cd8ead552ed59052-Abstract-Conference.html) | [Pytorch](https://github.com/ForestsKing/D3R) 
![Stars](https://img.shields.io/github/stars/ForestsKing/D3R?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ForestsKing/D3R?color=critical&style=social) | NIPS 2023

|  Anomaly Detection |SWaT 
  WADI 
  PSM 
 MSL 
  SMD 
 trimSyn |   Framework        | [Nominality Score Conditioned Time Series Anomaly Detection by Point/Sequential Reconstruction](https://proceedings.neurips.cc/paper_files/paper/2023/hash/22f5d8e689d2a011cd8ead552ed59052-Abstract-Conference.html) | [Pytorch](https://github.com/andrewlai61616/NPSR) 
![Stars](https://img.shields.io/github/stars/andrewlai61616/NPSR?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/andrewlai61616/NPSR?color=critical&style=social) | NIPS 2023

|  Anomaly Detection | SMD 
 MSL 
 SMAP 
 PSM  
  DND|   PUAD        | [Prototype-oriented unsupervised anomaly detection for multivariate time series](https://proceedings.mlr.press/v202/li23d.html) | [Pytorch](https://github.com/LiYuxin321/PUAD) 
![Stars](https://img.shields.io/github/stars/LiYuxin321/PUAD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LiYuxin321/PUAD?color=critical&style=social) | ICML 2023

|  Anomaly Detection |UCR 
SMD |   surrogate        | [Unsupervised Model Selection for Time Series Anomaly Detection](https://openreview.net/forum?id=gOZ_pKANaPW) | [Author](https://github.com/mononitogoswami) | ICLR 2023

|  Anomaly Detection | MSL 
   SMAP 
  PSM  
 SMD |   DCdetector        | [DCdetector: Dual Attention Contrastive Representation Learning for Time Series Anomaly Detection](https://dl.acm.org/doi/10.1145/3580305.3599295) | [Pytorch](https://github.com/DAMO-DI-ML/KDD2023-DCdetector) 
![Stars](https://img.shields.io/github/stars/DAMO-DI-ML/KDD2023-DCdetector?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DAMO-DI-ML/KDD2023-DCdetector?color=critical&style=social) | KDD 2023

|  Anomaly Detection | MSL 
   SWaT  
  WADI   |   PoA        | [Precursor-of-Anomaly Detection for Irregular Time Series](https://dl.acm.org/doi/10.1145/3580305.3599469) | [Pytorch](https://github.com/sheoyon-jhin/PAD) 
![Stars](https://img.shields.io/github/stars/sheoyon-jhin/PAD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sheoyon-jhin/PAD?color=critical&style=social) | KDD 2023

|  Anomaly Detection | MSL 
   SWaT  
  PSM 
   SMAP  
  SMD    |   DiffAD        | [Imputation-based Time-Series Anomaly Detection with Conditional Weight-Incremental Diffusion Models](https://doi.org/10.1145/3580305.3599391) | [Pytorch](https://github.com/ChunjingXiao/DiffAD) 
![Stars](https://img.shields.io/github/stars/ChunjingXiao/DiffAD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ChunjingXiao/DiffAD?color=critical&style=social) | KDD 2023

|  Anomaly Detection |SMD 
 SMAP 
 MSL 
 SWaT  |        DAEMON        | [Adversarial Autoencoder for Unsupervised Time Series Anomaly Detection and Interpretation](https://doi.org/10.1145/3539597.3570371) | [Pytorch](https://github.com/Sherlock-C/DAEMON) 
![Stars](https://img.shields.io/github/stars/Sherlock-C/DAEMON?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Sherlock-C/DAEMON?color=critical&style=social) | AAAI 2023

|  Anomaly Detection |  SWaT 
 WADI 
 PSM  
 MSL 
 SMD |        MTGFlow        | [Detecting Multivariate Time Series Anomalies with Zero Known Label](https://ojs.aaai.org/index.php/AAAI/article/view/25623) | [Pytorch](https://github.com/zqhang/MTGFLOW) 
![Stars](https://img.shields.io/github/stars/zqhang/MTGFLOW?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zqhang/MTGFLOW?color=critical&style=social) | AAAI 2023

|  Anomaly Detection |  SWaT 
 WADI  SMAP 
  MSL |        DuoGAT        | [DuoGAT: Dual Time-oriented Graph Attention Networks for Accurate, Efficient and Explainable Anomaly Detection on Time-series](https://dl.acm.org/doi/10.1145/3583780.3614857) | [Pytorch](https://github.com/ByeongtaePark/DuoGAT) 
![Stars](https://img.shields.io/github/stars/ByeongtaePark/DuoGAT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ByeongtaePark/DuoGAT?color=critical&style=social) | CIKM 2023

|  Anomaly Detection | SWaT 
   SMAP  
  MSL  
   PSM  
  SMD  |        MadSGM        | [MadSGM: Multivariate Anomaly Detection with Score-based Generative Models](https://dl.acm.org/doi/10.1145/3583780.3614857) | None  | CIKM 2023

|  Anomaly Detection |SMD 
 Boiler  |        ContexTDA        | [Context-aware Domain Adaptation for Time Series Anomaly Detection](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch76) | None| SDM 2023

|  Anomaly Detection | AIOps 
   UCR    |   COCA        | [Deep Contrastive One-Class Time Series Anomaly Detection](https://epubs.siam.org/doi/abs/10.1137/1.9781611977653.ch78) | [Merlion,Tsaug ](https://github.com/ruiking04/COCA) 
![Stars](https://img.shields.io/github/stars/ruiking04/COCA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ruiking04/COCA?color=critical&style=social) | SDM 2023

|  Anomaly Detection | DND 
 SMD 
 MSL 
 SMAP |        DVGCRN        | [Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection](https://proceedings.mlr.press/v162/chen22x.html) | [Future](https://github.com/BoChenGroup) | ICML 2022

|  Anomaly Detection | YelpChi 
 Amazon 
 T-Finance 
 T-Social  |        BWGNN        | [Rethinking Graph Neural Networks for Anomaly Detection](https://proceedings.mlr.press/v162/tang22b.html) | [Pytorch](https://github.com/squareRoot3/Rethinking-Anomaly-Detection) 
![Stars](https://img.shields.io/github/stars/squareRoot3/Rethinking-Anomaly-Detection?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/squareRoot3/Rethinking-Anomaly-Detection?color=critical&style=social) | ICML 2022

|  Anomaly Detection | SMD 
 PSM 
 MSL&SMAP 
 SWaT  
 NeurIPS-TS |         Anomaly Transformer        | [Anomaly Transformer: Time Series Anomaly Detection with Association Discrepancy](https://openreview.net/forum?id=LzQQ89U1qm_) | [Pytorch](https://github.com/spencerbraun/anomaly_transformer_pytorch) 
![Stars](https://img.shields.io/github/stars/spencerbraun/anomaly_transformer_pytorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/spencerbraun/anomaly_transformer_pytorch?color=critical&style=social) | ICLR 2022

| Density Estimation & Anomaly Detection | PMU-B 
 PMU-C 
 SWaT 
 METR-LA |         GANF        | [Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series](https://openreview.net/forum?id=45L_dgP48Vd) | [Pytorch](https://github.com/EnyanDai/GANF) 
![Stars](https://img.shields.io/github/stars/EnyanDai/GANF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/EnyanDai/GANF?color=critical&style=social) | ICLR 2022

|  Anomaly Detection |    |          | [Anomaly Detection for Tabular Data with Internal Contrastive Learning](https://openreview.net/forum?id=_hszZbt46bT) | None | ICLR 2022

|  Anomaly Detection |  Machine-Temp 
 NYCTaxi  
 Twitter 
 SWaT |       algorithmic   | [Local Evaluation of Time Series Anomaly Detection Algorithms](https://doi.org/10.1145/3534678.3539339) | [Python](https://github.com/ahstat/affiliation-metrics-py) 
![Stars](https://img.shields.io/github/stars/ahstat/affiliation-metrics-py?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ahstat/affiliation-metrics-py?color=critical&style=social) | KDD 2022

|  Anomaly Detection |  SWaT 
 WADI  
 HAI |       FuSAGNet   | [Learning Sparse Latent Graph Representations for Anomaly Detection in Multivariate Time Series](https://doi.org/10.1145/3534678.3539117) | [Pytorch](https://github.com/sihohan/FuSAGNet) 
![Stars](https://img.shields.io/github/stars/sihohan/FuSAGNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sihohan/FuSAGNet?color=critical&style=social)  | KDD 2022

|  Anomaly Detection |   Slef-defined  |       RCAD   | [RCAD: Real-time Collaborative Anomaly Detection System for Mobile Broadband Networks](https://doi.org/10.1145/3534678.3539097) | [Pytorch](https://github.com/azza8903/HTM-MODEL_EXCHANGE/) 
![Stars](https://img.shields.io/github/stars/azza8903/HTM-MODEL_EXCHANGE/?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/azza8903/HTM-MODEL_EXCHANGE/?color=critical&style=social) | KDD 2022

|  Anomaly Detection |     |       AnomalyKiTS   | [AnomalyKiTS-Anomaly Detection Toolkit for Time Series](https://aaai-2022.virtualchair.net/poster_dm318) | None | AAAI 2022

|  Anomaly Detection |  SWaT 
 WADI 
 MSL 
 SMAP 
 SMD  |       PA   | [Towards a Rigorous Evaluation of Time-Series Anomaly Detection](https://aaai-2022.virtualchair.net/poster_aaai2239) |  None  | AAAI 2022

|  Anomaly Detection | YAHOO 
 SMAP 
 MSL 
 PSM  |      NCAD    | [Neural Contextual Anomaly Detection for Time Series](https://doi.org/10.24963/ijcai.2022/332) |   [Future](https://github.com/awslabs/gluon-ts/tree/dev/src/gluonts/nursery)   | IJCAI 2022

|  Anomaly Detection | SWaT 
 WADI 
 SMD 
 PSM  |      GRELEN    | [GRELEN: Multivariate Time Series Anomaly Detection from the Perspective of Graph Relational Learning](https://doi.org/10.24963/ijcai.2022/394) | None| IJCAI 2022

|  Anomaly Detection | MSL 
 SMAP 
 MNIST 
 ,etc  |      CADET    | [CADET: Calibrated Anomaly Detection for Mitigating Hardness Bias](https://doi.org/10.24963/ijcai.2022/278) | [Future](https://github.com/d-ailin/CADET)| IJCAI 2022

|  Anomaly Detection | ECG 
 HAR 
 MNIST  |          | [Understanding and Mitigating Data Contamination in Deep Anomaly Detection: A Kernel-based Approach](https://doi.org/10.24963/ijcai.2022/322) | None | IJCAI 2022

|  Anomaly Detection | Business|       SLA-VAE       | [A Semi-Supervised VAE Based Active Anomaly Detection Framework in Multivariate Time Series for Online Systems](https://doi.org/10.1145/3485447.3511984) | None| WWW 2022

|  Anomaly Detection |  KDDCUP99 
  NSL   
  UNSW, etc |      MemStream       | [MemStream: Memory-Based Streaming Anomaly Detection](https://doi.org/10.1145/3485447.3511984) |  [Pytorch](https://github.com/Stream-AD/MemStream)| 
![Stars](https://img.shields.io/github/stars/Stream-AD/MemStream?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Stream-AD/MemStream?color=critical&style=social) WWW 2022

|  Anomaly Detection | GD 
 HSS 
 ECG 
 NAB 
 Yahoo S5 
  2D 
  SYN |        RDAE        | [Robust and Explainable Autoencoders for Unsupervised Time Series Outlier Detection](https://ieeexplore.ieee.org/document/9835554) | [Author](https://github.com/tungk) | ICDE 2022

|  Anomaly Detection | GD 
 HSS 
 ECG 
 TD 
 Yahoo S5   |        BiVQRAEs        | [Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders](https://ieeexplore.ieee.org/document/9835268) | [Pytorch](https://github.com/tungk/Bi-VQRAE) 
![Stars](https://img.shields.io/github/stars/tungk/Bi-VQRAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tungk/Bi-VQRAE?color=critical&style=social) | ICDE 2022

|  Anomaly Detection | SWaT 
 WADI 
 BATADAL  |        MAD-SGCN        | [MAD-SGCN: Multivariate Anomaly Detection with Self-learning Graph Convolutional Networks](https://ieeexplore.ieee.org/abstract/document/9835470) | None  | ICDE 2022

|  Anomaly Detection | NAB 
 UCR 
 MBA 
 SMAP 
  MSL 
 SWaT 
 WADI 
 SMD 
 MSDS   |       TranAD     | [TranAD: Deep Transformer Networks for Anomaly Detection in Multivariate Time Series Data](https://doi.org/10.14778/3514061.3514067) | [Pytorch](https://github.com/imperial-qore/TranAD) 
![Stars](https://img.shields.io/github/stars/imperial-qore/TranAD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/imperial-qore/TranAD?color=critical&style=social) | VLDB 2022

|  Anomaly Detection | KPI 
 Yahoo 
 SMAP 
 MSL   |       TFAD     | [TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis](https://doi.org/10.1145/3511808.3557470) | [Pytorch](https://github.com/damo-di-ml/cikm22-tfad) 
![Stars](https://img.shields.io/github/stars/damo-di-ml/cikm22-tfad?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/damo-di-ml/cikm22-tfad?color=critical&style=social) | CIKM 2022

|  Anomaly Detection | SMAP 
 MSL 
 SMD 
 KARI 
 Synthetic  |       Attack     | [Towards an Awareness of Time Series Anomaly Detection Models' Adversarial Vulnerability](https://doi.org/10.1145/3511808.3557073) | [Pytorch](https://github.com/shahroztariq/Adversarial-Attacks-on-Timeseries) 
![Stars](https://img.shields.io/github/stars/shahroztariq/Adversarial-Attacks-on-Timeseries?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/shahroztariq/Adversarial-Attacks-on-Timeseries?color=critical&style=social) | CIKM 2022

|  Anomaly Detection | Cora 
 Citeseer 
 PubMed 
 Flickr 
 ogbn-arxiv   |       LHML     | [Learning Hypersphere for Few-shot Anomaly Detection on Attributed Networks](https://doi.org/10.1145/3511808.3557377) | [Pytorch](https://github.com/Eureka-GQY/LHML) 
![Stars](https://img.shields.io/github/stars/Eureka-GQY/LHML?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Eureka-GQY/LHML?color=critical&style=social) | CIKM 2022

|  Anomaly Detection | RT 
 NetSpd   |       RobustDTW     | [Robust Time Series Dissimilarity Measure for Outlier Detection and Periodicity Detection](https://doi.org/10.1145/3511808.3557686) | None | CIKM 2022

|  Anomaly Detection |  CIFAR-1 
  CIFAR-10  
   Caltech 10  |        SLA2     | [Self-supervision Meets Adversarial Perturbation: A Novel Framework for Anomaly Detection](https://doi.org/10.1145/3511808.3557697) | [Pytorch](https://github.com/wyzjack/SLA2P) 
![Stars](https://img.shields.io/github/stars/wyzjack/SLA2P?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/wyzjack/SLA2P?color=critical&style=social) | CIKM 2022

|  Anomaly Detection |  SMD  |       FDRC   | [Online false discovery rate control for anomaly detection in time series](https://dl.acm.org/doi/10.1145/3447548.3467075) | Nçone  | NeurIPS 2021

|  Anomaly Detection |  SWaT 
 WADI 
 SMD 
 ASD  |       InterFusion   | [Multivariate Time Series Anomaly Detection and Interpretation using Hierarchical Inter-Metric and Temporal Embedding](https://papers.NeurIPS.cc/paper/2021/hash/def130d0b67eb38b7a8f4e7121ed432c-Abstract.html) |  [TF](https://github.com/zhhlee/InterFusion)  
![Stars](https://img.shields.io/github/stars/zhhlee/InterFusion?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhhlee/InterFusion?color=critical&style=social) | KDD 2021

|  Anomaly Detection |  SMD 
 SWaT 
 PSM 
 BKPI  |       RANSynCoders   | [Practical Approach to Asynchronous Multivariate Time Series Anomaly Detection and Localization](https://doi.org/10.1145/3447548.3467174) |  [TF](https://github.com/eBay/RANSynCoders)  
![Stars](https://img.shields.io/github/stars/eBay/RANSynCoders?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/eBay/RANSynCoders?color=critical&style=social) | KDD 2021

|  Anomaly Detection |  PUMP 
 WADI 
 SWaT  |       NSIBF   | [Time Series Anomaly Detection for Cyber-physical Systems via Neural System Identification and Bayesian Filtering](https://doi.org/10.1145/3447548.3467137) |  [TF](https://github.com/NSIBF/NSIBF)  
![Stars](https://img.shields.io/github/stars/NSIBF/NSIBF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NSIBF/NSIBF?color=critical&style=social) | KDD 2021

|  Anomaly Detection |  SWaT 
 WADI   |       GDN   | [Graph Neural Network-Based Anomaly Detection in Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/16523) |  [Pytorch](https://github.com/d-ailin/GDN)  
![Stars](https://img.shields.io/github/stars/d-ailin/GDN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/d-ailin/GDN?color=critical&style=social) | AAAI 2021

|  Anomaly Detection | SMD 
 SMAP 
 MSL 
 SWaT  |       DAEMON   | [DAEMON: Unsupervised Anomaly Detection and Interpretation for Multivariate Time Series](https://ieeexplore.ieee.org/abstract/document/9458835) |  [Future](https://github.com/Azerrroth/DAEMON)  | ICDE 2021

|  Anomaly Detection |  KPI 
 Yahoo   |      FluxEV   | [FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection](https://doi.org/10.1145/3437963.3441823) |   [Py](https://github.com/jlidw/FluxEV)  | WSDM 2021

|  Anomaly Detection | [DataLink](https://compete.hexagon-ml.com/practice/competition/39/)|        Benchmark        | [Current Time Series Anomaly Detection Benchmarks are Flawed and are Creating the Illusion of Progress](https://ieeexplore.ieee.org/abstract/document/9537291) | None | TKDE 2021

|  Earthquakes Detection |  NIED   |       CrowdQuake   | [A Networked System of Low-Cost Sensors for Earthquake Detection via Deep Learning](https://doi.org/10.1145/3394486.3403378) |  [TF](https://github.com/xhuang2016/Seismic-Detection)    
![Stars](https://img.shields.io/github/stars/xhuang2016/Seismic-Detection?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/xhuang2016/Seismic-Detection?color=critical&style=social) | KDD 2020

|  Anomaly Detection |  SWaT  
 WADI 
 SMD  
  SMAP 
 MSL 
  Orange |       USAD   | [USAD: UnSupervised Anomaly Detection on Multivariate Time Series](https://doi.org/10.1145/3394486.3403392) |   [Pytorch](https://github.com/manigalati/usad)   
![Stars](https://img.shields.io/github/stars/manigalati/usad?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/manigalati/usad?color=critical&style=social) | KDD 2020

|  Anomaly Detection |  NYC  |       CHAT   | [Cross-interaction hierarchical attention networks for urban anomaly prediction](https://dl.acm.org/doi/abs/10.5555/3491440.3492041) |  None  | IJCAI 2020

|  Anomaly Detection |  NYC-Bike  
 NYC-Taxi 
 Weather 
  NYC-POI 
 NYC-Anomaly |       DST-MFN   | [Deep Spatio-Temporal Multiple Domain Fusion Network for Urban Anomalies Detection](https://doi.org/10.1145/3340531.3411920) |  None  | CIKM 2020

|  Anomaly Detection | SMAP 
 MSL 
 TSA  |      MTAD-GAT | [Multivariate Time-Series Anomaly Detection via Graph Attention Network](https://ieeexplore.ieee.org/abstract/document/9338317) |   [TF](https://github.com/mangushev/mtad-gat)  
![Stars](https://img.shields.io/github/stars/mangushev/mtad-gat?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/mangushev/mtad-gat?color=critical&style=social) [Pytorch](https://github.com/ML4ITS/mtad-gat-pytorch) | ICDM 2020

|  Anomaly Detection |  SMAP  
 MSL 
 SMD  |       OmniAnomaly   | [Robust Anomaly Detection for Multivariate Time Series through Stochastic Recurrent Neural Network](https://doi.org/10.1145/3292500.3330672) |   [TF](https://github.com/NetManAIOps/OmniAnomaly)   
![Stars](https://img.shields.io/github/stars/NetManAIOps/OmniAnomaly?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NetManAIOps/OmniAnomaly?color=critical&style=social) | KDD 2019

|  Anomaly Detection |  GeoLife  
 TST   |       IRL-ADU   | [Sequential Anomaly Detection using Inverse Reinforcement Learning](https://doi.org/10.1145/3292500.3330932) |   None  | KDD 2019

|  Anomaly Detection |  donors  
 census  
 fraud 
 celeba ,etc |      DevNet  | [Deep Anomaly Detection with Deviation Networks](https://doi.org/10.1145/3292500.3330871) |   [Keras](https://github.com/GuansongPang/deviation-network) 
![Stars](https://img.shields.io/github/stars/GuansongPang/deviation-network?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GuansongPang/deviation-network?color=critical&style=social) [Pytorch](https://github.com/Choubo/deviation-network-image) | KDD 2019

|  Anomaly Detection | KPI 
 Yahoo 
 Microsoft  |      SR-CNN  | [Time-Series Anomaly Detection Service at Microsoft](https://doi.org/10.1145/3292500.3330680) |   None | KDD 2019

|  Anomaly Detection |  power plant |      MSCRED  | [A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data](https://ojs.aaai.org/index.php/AAAI/article/view/3942) |   [TF](https://github.com/7fantasysz/MSCRED) 
![Stars](https://img.shields.io/github/stars/7fantasysz/MSCRED?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/7fantasysz/MSCRED?color=critical&style=social) | AAAI 2019

|  Anomaly Detection | ECG 
 Motion |      BeatGAN  | [BeatGAN: Anomalous Rhythm Detection using Adversarially Generated Time Series](https://www.ijcai.org/Proceedings/2019/0616.pdf) |   [Pytorch](https://github.com/hi-bingo/BeatGAN) 
![Stars](https://img.shields.io/github/stars/hi-bingo/BeatGAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hi-bingo/BeatGAN?color=critical&style=social) | IJCAI 2019

|  Anomaly Detection | NAB 
 ECG |      OED  | [Outlier Detection for Time Series with Recurrent Autoencoder Ensembles](https://www.ijcai.org/proceedings/2019/0378.pdf) |   [TF](https://github.com/tungk/OED) 
![Stars](https://img.shields.io/github/stars/tungk/OED?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tungk/OED?color=critical&style=social) | IJCAI 2019

|  Anomaly Detection | KPIs |      Buzz  | [Unsupervised Anomaly Detection for Intricate KPIs via Adversarial Training of VAE](https://ieeexplore.ieee.org/abstract/document/8737430) |   [TF](https://github.com/yantijin/Buzz) 
![Stars](https://img.shields.io/github/stars/yantijin/Buzz?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yantijin/Buzz?color=critical&style=social) | INFOCOM 2019

|  Anomaly Detection | KDDCUP 
 Thyroid 
 Arrhythmia  
 KDDCUP-Rev |      DAGMM  | [Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection](https://openreview.net/forum?id=BJJLHbb0-) |   [Pytorch](https://github.com/danieltan07/dagmm) 
![Stars](https://img.shields.io/github/stars/danieltan07/dagmm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/danieltan07/dagmm?color=critical&style=social) | ICLR 2018

|  Anomaly Detection | SMAP 
 MSL  |      telemanom  | [Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding](https://doi.org/10.1145/3219819.3219845) |   [TF](https://github.com/khundman/telemanom) 
![Stars](https://img.shields.io/github/stars/khundman/telemanom?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/khundman/telemanom?color=critical&style=social) | KDD 2018

|  Anomaly Detection | AD 
 AID362 
 aPascal  
  BM , etc|      CINFO | [Sparse Modeling-Based Sequential Ensemble Learning for Effective Outlier Detection in High-Dimensional Numeric Data](https://ojs.aaai.org/index.php/AAAI/article/view/11692) |    [Matlab](https://drive.google.com/file/d/0B_GL5U7rPj1xNzNwTHpHSzZkQXM/view?resourcekey=0-HneFEhC8NUIWDfhmfaOyBQ) | AAAI 2018

|  Anomaly Detection | KPIs |      Donut | [Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications](https://doi.org/10.1145/3178876.3185996) |    [TF](https://github.com/NetManAIOps/donut) 
![Stars](https://img.shields.io/github/stars/NetManAIOps/donut?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NetManAIOps/donut?color=critical&style=social) | WWW 2018

|  Anomaly Detection | MAWI |      DSPOT | [Anomaly Detection in Streams with Extreme Value Theory](https://doi.org/10.1145/3097983.3098144) |    [Python](https://github.com/NetManAIOps/donut) 
![Stars](https://img.shields.io/github/stars/NetManAIOps/donut?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NetManAIOps/donut?color=critical&style=social) | KDD 2017

|  Anomaly Detection | Power 
 Space 
  Engine 
 ECG |         EncDec-AD | [    LSTM-based encoder-decoder for multi-sensor anomaly detection](https://www.semanticscholar.org/paper/LSTM-based-Encoder-Decoder-for-Multi-sensor-Anomaly-Malhotra-Ramakrishnan/e9672150c4f39ab64876e798a94212a93d1770fe) |    [Pytorch](https://github.com/jaeeun49/Anomaly-Detection/blob/main/code_practices/LSTM-based%20Encoder-Decoder%20for%20Multi-sensor%20Anomaly%20Detection.ipynb) | ICML 2016

|  Anomaly Detection |  MORE  |       MORE   | [https://github.com/ZIYU-DEEP/IJCAI-Paper-List-of-Anomaly-Detection](https://github.com/ZIYU-DEEP/IJCAI-Paper-List-of-Anomaly-Detection) |  MORE   | IJCAI

|  Anomaly Detection |  MORE  |       MORE   | [DeepTimeSeriesModel](https://github.com/drzhang3/DeepTimeSeriesModel) |  MORE   | MORE

|  Anomaly Detection |  MORE  |       MORE   | [GuansongPang](https://github.com/GuansongPang/SOTA-Deep-Anomaly-Detection) |  MORE   | MORE

# [Demand Prediction](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-:| - |

| Paper Nums: 30+ |  |   |   |   |    |

| Travel 
 Demand  |  CDP  
 SLD |       STTD    | [Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction](https://dl.acm.org/doi/10.1145/3583780.3614918) | [Pytorch](https://github.com/STTDAnonymous/STTD) 
![Stars](https://img.shields.io/github/stars/STTDAnonymous/STTD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/STTDAnonymous/STTD?color=critical&style=social) | CIKM 2023

| Travel 
 Demand  |  NYC Bike  
 NYC Taxi |       AGND    | [Adaptive Graph Neural Diffusion for Traffic Demand Forecasting](https://dl.acm.org/doi/abs/10.1145/3583780.3615153) | None | CIKM 2023

| Traffic Demand | BJSubway 
 NYCTaxi |        CMOD | [Continuous-Time and Multi-Level Graph Representation Learning for Origin-Destination Demand Prediction](https://doi.org/10.1145/3534678.3539273) | [Pytorch](https://github.com/liangzhehan/CMOD) 
![Stars](https://img.shields.io/github/stars/liangzhehan/CMOD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liangzhehan/CMOD?color=critical&style=social) | KDD 2022

| Job Demand | IT 
 FIN 
 CONS |        DH-GEM | [Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning](https://doi.org/10.1145/3534678.3539139) | [Pytorch](https://github.com/gzn00417/DH-GEM) 
![Stars](https://img.shields.io/github/stars/gzn00417/DH-GEM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gzn00417/DH-GEM?color=critical&style=social) | KDD 2022

| Supply & 
 Demand | JONAS-NYC 
 JONAS-DC  
  COVID-CHI 
  COVID-US |         EAST-Net | [Event-Aware Multimodal Mobility Nowcasting](https://aaai-2022.virtualchair.net/poster_aaai10914) | [Pytorch](https://github.com/underdoc-wang/EAST-Net) 
![Stars](https://img.shields.io/github/stars/underdoc-wang/EAST-Net?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/underdoc-wang/EAST-Net?color=critical&style=social) | AAAI 2022

| Health Demand | Family Van  |         framework        | [Using Public Data to Predict Demand for Mobile Health Clinics](https://aaai-2022.virtualchair.net/poster_emer91) | None | AAAI 2022

| Traffic Demand  | BJMetro 
 NYCTaxi  |       HMOD      | [Dynamic Graph Learning Based on Hierarchical Memory for Origin-Destination Demand Prediction](https://doi.org/10.24963/ijcai.2022/331) |   [Pytorch](https://github.com/Rising0321/HMOD)  
![Stars](https://img.shields.io/github/stars/Rising0321/HMOD?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Rising0321/HMOD?color=critical&style=social) | IJCAI 2022

| Traffic Demand  | Chicago  
 LosAngeles  |       STGNN-DJD      | [A Data-Driven Spatial-Temporal Graph Neural Network for Docked Bike Prediction](https://ieeexplore.ieee.org/abstract/document/9835338) |   [Pytorch](https://github.com/GuanyaoLI/STGNN)  
![Stars](https://img.shields.io/github/stars/GuanyaoLI/STGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GuanyaoLI/STGNN?color=critical&style=social) | ICDE 2022

| OD Demand  | Shanghai  
 Changsha 
 Beijing  |    CausalOD     | [Causal Learning Empowered OD Prediction for Urban Planning](https://doi.org/10.1145/3511808.3557255) |   [Pytorch](https://github.com/tsinghua-fib-lab/SIRI)  
![Stars](https://img.shields.io/github/stars/tsinghua-fib-lab/SIRI?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tsinghua-fib-lab/SIRI?color=critical&style=social) | CIKM 2022

| OD Demand  | NYC Taxi  
 Haikou 
 SZMetro  |    HSTN     | [Origin-Destination Traffic Prediction based on Hybrid Spatio-Temporal Network](https://ieeexplore.ieee.org/document/10027683) |   [TF](https://github.com/chentingyang/HSTN)  
![Stars](https://img.shields.io/github/stars/chentingyang/HSTN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chentingyang/HSTN?color=critical&style=social) | ICDM 2022

| Traffic Demand | NYC Bike 
 NYC Taxi  |         CCRNN        | [Coupled Layer-wise Graph Convolution for Transportation Demand Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/16591) | [Pytorch](https://github.com/Essaim/CGCDemandPrediction) 
![Stars](https://img.shields.io/github/stars/Essaim/CGCDemandPrediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Essaim/CGCDemandPrediction?color=critical&style=social) | AAAI 2021

| Traffic Demand | BaiduBJ  
 BaiduSH  |         Ada-MSTNet        | [Community-Aware Multi-Task Transportation Demand Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/16107) | None | AAAI 2021

| Job Demand | Online |         TDAN       | [Talent Demand Forecasting with Attentive Neural Sequential Model](https://dl.acm.org/doi/abs/10.1145/3447548.3467131) | None | KDD 2021

| Ambulance Demand | Tokyo |         EMS-Pred       | [Forecasting Ambulance Demand with Profiled Human Mobility via Heterogeneous Multi-Graph Neural Networks](https://ieeexplore.ieee.org/abstract/document/9458623) |  [Pytorch](https://github.com/underdoc-wang/EMS-Pred-ICDE-21)  
![Stars](https://img.shields.io/github/stars/underdoc-wang/EMS-Pred-ICDE-21?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/underdoc-wang/EMS-Pred-ICDE-21?color=critical&style=social) | ICDE 2021

| Passenger Demand | TaxiNYC |        SOUP     | [SOUP: A Fleet Management System for Passenger Demand Prediction and Competitive Taxi Supply](https://ieeexplore.ieee.org/abstract/document/9458616) |  None  | ICDE 2021

| Passenger Demand |  DiDiBJ 
 DiDiSH|        Gallat     | [Gallat: A Spatiotemporal Graph Attention Network for Passenger Demand Prediction](https://ieeexplore.ieee.org/document/9458919) |  None  | ICDE 2021

| Traffic Demand 
 Traffic Flow |  Chengdu  
 Xian|        DeepTP     | [An Effective Joint Prediction Model for Travel Demands and Traffic Flows](https://ieeexplore.ieee.org/document/9458698) |  None  | ICDE 2021

| Traffic  Demand | DiDiCD 
 NYCTaxi |         DAGNN       | [Dynamic Auto-structuring Graph Neural Network-A Joint Learning Framework for Origin-Destination Demand Prediction](https://ieeexplore.ieee.org/abstract/document/9657493) | None   | TKDE 2021

| Traffic Demand  |  TaxiNYC 
  CitiBikeNYC |        MultiAttConvLSTM          | [Multi-level attention networks for multi-step citywide passenger demands prediction](https://ieeexplore.ieee.org/abstract/document/8873676/) | None  | TKDE 2021

| Market Demand  |  Juhuasuan  
 Tiantiantemai     |        RMLDP    | [Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records](https://doi.org/10.1145/3437963.3441750) |    None  | WSDM 2021

| Metro  Demand | MetroBJ2016 
 MetroBJ2018 |         CAS       | [Short-term origin-destination demand prediction in urban rail transit systems: A channel-wise attentive split-convolutional neural network method](https://doi.org/10.1016/j.trc.2020.102928) |  None   |  Transportation Research Part C 2021

| Metro  Demand | MetroBJ2016 
 MetroBJ2018 |         ST-ED       | [Predicting origin-destination ride-sourcing demand with a spatio-temporal encoder-decoder residual multi-graph convolutional network](https://doi.org/10.1016/j.trc.2020.102858) |  None   |  Transportation Research Part C 2021

| Traffic Demand |  Seattlebike  |       FairST      | [Fairness-Aware Demand Prediction for New Mobility](https://ojs.aaai.org/index.php/AAAI/article/view/5458) | None | AAAI 2020

| Drug Demand  |  Wikipedia  |        None          | [Predicting Drug Demand with Wikipedia Views: Evidence from Darknet Markets](https://doi.org/10.1145/3366423.3380022) | None  | WWW 2020

| Traffic Demand  | DiDiBJ  
  DiDiSH  |  MPGCN   | [Predicting Origin-Destination Flow via Multi-Perspective Graph Convolutional Network](https://ieeexplore.ieee.org/abstract/document/9101359) | [Pytorch](https://github.com/underdoc-wang/MPGCN)  
![Stars](https://img.shields.io/github/stars/underdoc-wang/MPGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/underdoc-wang/MPGCN?color=critical&style=social) | ICDE 2020

| Traffic Demand  | NYC  
  DiDiCD  |  MPGCN   | [Stochastic Origin-Destination Matrix Forecasting Using Dual-Stage Graph Convolutional, Recurrent Neural Networks](https://ieeexplore.ieee.org/abstract/document/9101647/) | [TF](https://github.com/hujilin1229/od-pred)  
![Stars](https://img.shields.io/github/stars/hujilin1229/od-pred?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hujilin1229/od-pred?color=critical&style=social) | ICDE 2020

| Traffic Demand  | Bengaluru  
  NYC  |  GraphLSTM   | [Grids Versus Graphs: Partitioning Space for Improved Taxi Demand-Supply Forecasts](https://ieeexplore.ieee.org/abstract/document/9099450/) | [Pytorch](https://github.com/NDavisK/Grids-versus-Graphs)  
![Stars](https://img.shields.io/github/stars/NDavisK/Grids-versus-Graphs?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NDavisK/Grids-versus-Graphs?color=critical&style=social) | TITS 2020

| Traffic Demand  | NYCbike  
  NYCtaxi  |  CoST-Net   | [Co-Prediction of Multiple Transportation Demands Based on Deep Spatio-Temporal Neural Network](https://doi.org/10.1145/3292500.3330887) | None  | KDD 2019

| Traffic Demand  | UCAR  
  DiDiCD  |  GEML   | [Origin-Destination Matrix Prediction via Graph Convolution: a New Perspective of Passenger Demand Modeling](https://doi.org/10.1145/3292500.3330877) | [Keras](https://github.com/Zekun-Cai/GEML-Origin-Destination-Matrix-Prediction-via-Graph-Convolution)   
![Stars](https://img.shields.io/github/stars/Zekun-Cai/GEML-Origin-Destination-Matrix-Prediction-via-Graph-Convolution?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Zekun-Cai/GEML-Origin-Destination-Matrix-Prediction-via-Graph-Convolution?color=critical&style=social) | KDD 2019

| Traffic Demand  | NYCbike  
  Meso West  |  CE-LSTM   | [Learning Heterogeneous Spatial-Temporal Representation for Bike-Sharing Demand Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/3890) | None | AAAI 2019

| Traffic Demand  | Beijing  
  Shanghai  |  STMGCN  | [Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/4247) | [Pytorch](https://github.com/underdoc-wang/ST-MGCN) 
![Stars](https://img.shields.io/github/stars/underdoc-wang/ST-MGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/underdoc-wang/ST-MGCN?color=critical&style=social) | AAAI 2019

| Traffic Demand  | NYC-TOD   |  CSTN  | [Contextualized Spatial–Temporal Network for Taxi Origin-Destination Demand Prediction](https://ieeexplore.ieee.org/abstract/document/8720246/) | [Keras](https://github.com/liulingbo918/CSTN) 
![Stars](https://img.shields.io/github/stars/liulingbo918/CSTN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liulingbo918/CSTN?color=critical&style=social) | TITS 2019

| Traffic Demand  | NYCtaxi   |  MultiConvLSTM  | [Deep Multi-Scale Convolutional LSTM Network for Travel Demand and Origin-Destination Predictions](https://ieeexplore.ieee.org/abstract/document/8758916/) |  None   | TITS 2019

| Traffic Demand  | PEMS   |  t-SNE  | [Estimating multi-year  origin-destination demand using high-granular multi-source traffic data](https://doi.org/10.1016/j.trc.2018.09.002) |  None   | Transportation Research Part C 2018

# [Time Series Generation](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums: 6  |  |      |     |     |   |

| TS Generation |  Stock  
 Energy  
  MuJoCo  |   ImagenTime       | [Utilizing Image Transforms and Diffusion Models for Generative Modeling of Short and Long Time Series](https://openreview.net/forum?id=2NfBBpbN9x) | [Pytorch](https://github.com/azencot-group/ImagenTime) 
![Stars](https://img.shields.io/github/stars/azencot-group/ImagenTime?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/azencot-group/ImagenTime?color=critical&style=social)  | NIPS 2024

| TS Generation | AR1 
  Stock  
 Energy  
  Temperature 
 ECG  |   FIDE       | [FIDE: Frequency-Inflated Conditional Diffusion Model for Extreme-Aware Time Series Generation](https://openreview.net/forum?id=5HQhYiGnYb) | [Pytorch](https://github.com/galib19/FIDE) 
![Stars](https://img.shields.io/github/stars/galib19/FIDE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/galib19/FIDE?color=critical&style=social)  | NIPS 2024

| TS Generation | Electricity 
  Traffic  
 Exchange  
  M4 
 UberTLC 
 Solar 
 KDDCup 
 Wikipedia |   ANT       | [ANT: Adaptive Noise Schedule for Time Series Diffusion Models](https://openreview.net/forum?id=1ojAkTylz4) | [glounts](https://github.com/seunghan96/ANT) 
![Stars](https://img.shields.io/github/stars/seunghan96/ANT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/seunghan96/ANT?color=critical&style=social)  | NIPS 2024

| TS Generation | Sines 
  Stocks  
 ETTh 
  MuJoCo 
 Energy 
 Solar 
 fMRI |   SDformer       | [SDformer: Similarity-driven Discrete Transformer For Time Series Generation](https://openreview.net/forum?id=ZKbplMrDzI) | [Pytorch](https://anonymous.4open.science/r/SDformer-main/README.md)  | NIPS 2024

| TS Generation | Sines 
  Stocks  
 ETTh 
  MuJoCo 
 Energy 
 Solar 
 fMRI |   Diffusion-TS        | [Diffusion-TS: Interpretable Diffusion for General Time Series Generation](https://openreview.net/forum?id=4h1apFjO99) | [Pytorch](https://github.com/Y-debug-sys/Diffusion-TS) 
![Stars](https://img.shields.io/github/stars/Y-debug-sys/Diffusion-TS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Y-debug-sys/Diffusion-TS?color=critical&style=social) | ICLR 2024

| TS Generation | FRED-MD 
 NN5 Daily 
 Temp Rain 
 Solar Weekly |   LS4        | [Deep Latent State Space Models for Time-Series Generation](https://proceedings.mlr.press/v202/zhou23i.html) | [Pytorch](https://github.com/thuwuyinjun/DGM2) 
![Stars](https://img.shields.io/github/stars/thuwuyinjun/DGM2?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuwuyinjun/DGM2?color=critical&style=social) | ICML 2023

| TS Generation  | He ́non maps 
 Lorenz  
 fMRI  
  EEG|        CR-VAE    | [Causal Recurrent Variational Autoencoder for Medical Time Series Generation](https://ojs.aaai.org/index.php/AAAI/article/view/26031) | [Pytorch](https://github.com/hongmingli1995/CR-VAE) 
![Stars](https://img.shields.io/github/stars/hongmingli1995/CR-VAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hongmingli1995/CR-VAE?color=critical&style=social)     | AAAI 2023

| TS Generation  | ETTh1  
 ETTh2  
 US Births  
  ILI|       AEC-GAN    | [AEC-GAN: Adversarial Error Correction GANs for Auto-Regressive Long Time-Series Generation](https://ojs.aaai.org/index.php/AAAI/article/view/26208) | [Pytorch](https://github.com/hongmingli1995/CR-VAE) 
![Stars](https://img.shields.io/github/stars/hongmingli1995/CR-VAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/hongmingli1995/CR-VAE?color=critical&style=social)     | AAAI 2023

| TS Generation | UCR  |   TimeVQVAE     | [Vector Quantized Time Series Generation with a Bidirectional Prior Model](https://proceedings.mlr.press/v206/lee23d.html) | [Pytorch](https://github.com/ML4ITS/TimeVQVAE) 
![Stars](https://img.shields.io/github/stars/ML4ITS/TimeVQVAE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/ML4ITS/TimeVQVAE?color=critical&style=social) | AISTATS 2023   

| TS Generation | USHCN 
 KDD-CUP 
 MIMIC-III|   DGM        | [Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/16145) | [Pytorch](https://github.com/thuwuyinjun/DGM2) 
![Stars](https://img.shields.io/github/stars/thuwuyinjun/DGM2?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thuwuyinjun/DGM2?color=critical&style=social) | AAAI 2021

# [Travel Time Estimation](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums:20+ |  |   |   |   |    |

| Package Delivery 
 TTE | Cainiao |        GMDNet       | [GMDNet: A Graph-Based Mixture Density Network for Estimating Packages’ Multimodal Travel Time Distribution](https://ojs.aaai.org/index.php/AAAI/article/view/25578) | [Pytorch](https://github.com/maoxiaowei97/GMDNet) 
![Stars](https://img.shields.io/github/stars/maoxiaowei97/GMDNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/maoxiaowei97/GMDNet?color=critical&style=social) | AAAI 2023

| Delivery 
 Time Estimation | Weihai 
 Hangzhou |        IGT       | [Inductive Graph Transformer for Delivery Time Estimation](https://doi.org/10.1145/3539597.3570409) | [Pytorch](https://github.com/enoche/IGT-WSDM23) 
![Stars](https://img.shields.io/github/stars/enoche/IGT-WSDM23?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/enoche/IGT-WSDM23?color=critical&style=social) | WSDM 2023

| Delivery 
 Time Estimation | JD and Amazon  |      STTD       | [Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction](https://dl.acm.org/doi/10.1145/3583780.3615215) | [Pytorch](https://github.com/JD-HST-GT/HST-GT) 
![Stars](https://img.shields.io/github/stars/JD-HST-GT/HST-GT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JD-HST-GT/HST-GT?color=critical&style=social) | CIKM 2023

| TTE |  Jinan City 
 Nanjing City |      GBTTE       | [GBTTE: Graph Attention Network Based Bus Travel Time Estimation](https://dl.acm.org/doi/10.1145/3583780.3614730) |  None  | CIKM 2023

| TTE | Beijing 
 Guangzhou |        HierETA       | [Interpreting Trajectories from Multiple Views: A Hierarchical Self-Attention Network for Estimating the Time of Arrival](https://doi.org/10.1145/3534678.3539051) | [Pytorch](https://github.com/YuejiaoGong/HierETA) 
![Stars](https://img.shields.io/github/stars/YuejiaoGong/HierETA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YuejiaoGong/HierETA?color=critical&style=social) | KDD 2022

| TTE | Beijing 
 Porto |         MetaER-TTE        | [MetaER-TTE: An Adaptive Meta-learning Model for En Route Travel Time Estimation](https://doi.org/10.24963/ijcai.2022/281) | None | IJCAI 2022

| TTE | Beijing 
 Shanghai 
 Tianjin |        DuETA       | [DuETA: Traffic Congestion Propagation Pattern Modeling via Efficient Graph Learning for ETA Prediction at Baidu Maps](https://doi.org/10.1145/3511808.3557091) | None | CIKM 2022

| TTE | Baidu:
 Taiyuan 
 Huizhou 
 Hefei|         SSML        | [SSML: Self-Supervised Meta-Learner for En Route Travel Time Estimation at Baidu Maps](https://dl.acm.org/doi/10.1145/3447548.3467060) | [Paddle](https://github.com/PaddlePaddle/Research/tree/master/ST_DM/KDD2021-SSML)  | KDD 2021

| TTE | DiDi: 
 Shenyang     |     HetETA        | [HetETA: Heterogeneous Information Network Embedding for Estimating Time of Arrival](https://dl.acm.org/doi/10.1145/3394486.3403294) | [TF](https://github.com/didi/heteta)  
![Stars](https://img.shields.io/github/stars/didi/heteta?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/didi/heteta?color=critical&style=social) | KDD 2020

| TTE | DiDi: 
 Beijing 
 Suzhou 
 Shenyang   |     CompactETA        | [CompactETA: A Fast Inference System for Travel Time Prediction](https://dl.acm.org/doi/10.1145/3394486.3403386) | None | KDD 2020

| TTE | GTFS     |     BusTr        | [BusTr: Predicting Bus Travel Times from Real-Time Traffic](https://doi.org/10.1145/3394486.3403376) |   None  | KDD 2020

| TTE | Taiyuan   
  Hefei 
 Huizhou 
 （Baidu）   |     BusTr        | [ConSTGAT: Contextual Spatial-Temporal Graph Attention Network for Travel Time Estimation at Baidu Maps](https://doi.org/10.1145/3394486.3403320) |   None  | KDD 2020

| TTE | NYC   
  IST 
 TKY   |     DeepJMT        | [Context-aware Deep Model for Joint Mobility and Time Prediction](https://doi.org/10.1145/3336191.3371837) |   None  | WSDM 2020

| TTE | Beijing 
 Shanghai    |     TTPNet        | [TTPNet: A Neural Network for Travel Time Prediction Based on Tensor Decomposition and Graph Embedding](https://ieeexplore.ieee.org/abstract/document/9261122) |   [Pytorch](https://github.com/YibinShen/TTPNet)  
![Stars](https://img.shields.io/github/stars/YibinShen/TTPNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YibinShen/TTPNet?color=critical&style=social) | TKDE 2020

| TTE | DiDiBJ   |     RNML-ETA         | [Road Network Metric Learning for Estimated Time of Arrival](https://ieeexplore.ieee.org/abstract/document/9412145) |   None  | ICPR 2020

| TTE | Cainiao    |     DeepETA       | [DeepETA: A Spatial-Temporal Sequential Neural Network Model for Estimating Time of Arrival in Package Delivery System](https://ojs.aaai.org/index.php/AAAI/article/view/3856) |   None  | AAAI 2019

| TTE | Beijing  
  Shanghai |     CTTE       | [Aggressive driving saves more time? Multi-task learning for customized travel time estimation](https://www.ijcai.org/Proceedings/2019/0234.pdf) |   None  | IJCAI 2019

| TTE | Shanghai  
  Porto |     DeepI2T       | [Travel time estimation without road networks: an urban morphological layout representation approach](https://www.ijcai.org/proceedings/2019/0245.pdf) |   None  | IJCAI 2019

| TTE | Porto 
 Chengdu    |     DeepIST        | [DeepIST: Deep Image-based Spatio-Temporal Network for Travel Time Estimation](https://dl.acm.org/doi/abs/10.1145/3357384.3357870) |   [TF](https://github.com/csiesheep/deepist)  
![Stars](https://img.shields.io/github/stars/csiesheep/deepist?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/csiesheep/deepist?color=critical&style=social) | CIKM 2019

| TTE | Singapore |     AtHy-TNet       | [Path Travel Time Estimation using Attribute-related Hybrid Trajectories Network](https://doi.org/10.1145/3357384.3357927) |   None  | CIKM 2019

| TTE | BT-Traffic 
 PEMS07 
  Q-traffic |    NASF     | [Learning to Effectively Estimate the Travel Time for Fastest Route Recommendation](https://doi.org/10.1145/3357384.3357907) |   None  | CIKM 2019

| TTE | Chengdu 
 Beijing    |     DeepTTE        | [When Will You Arrive? Estimating Travel Time Based on Deep Neural Networks](https://jelly007.github.io/deepTTE.pdf) |   [Pytorch](https://github.com/UrbComp/DeepTTE)  
![Stars](https://img.shields.io/github/stars/UrbComp/DeepTTE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/UrbComp/DeepTTE?color=critical&style=social) | AAAI 2018

| TTE | PORTO 
SANFRANCISCO  |    NoisyOR     | [Predicting Vehicular Travel Times by Modeling Heterogeneous Influences Between Arterial Roads](https://ojs.aaai.org/index.php/AAAI/article/view/11858) |   None  | AAAI 2018

| TTE |  MORE  |     MORE       | [github](https://github.com/NickHan-cs/Spatio-Temporal-Data-Mining-Survey/blob/master/Estimated-Time-of-Arrival/Paper.md) | MORE | MORE

# [Traffic Location Prediction](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: |:-: | - |

| Paper Nums:20 |  |   |   |   |    |

| Location | ETH+UCY 
 SDD 
 nuScenes 
 SportVU |              | [You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction](https://openreview.net/forum?id=POxF-LEqnF) | None | ICLR 2022

| Location | Beijing 
 Porto  |     MetaPTP         | [MetaPTP: An Adaptive Meta-optimized Model for Personalized Spatial Trajectory Prediction](https://doi.org/10.1145/3534678.3539360) |  [Kai Zheng](http://zheng-kai.com/) Code-None | KDD 2022

| Location | BaiduApollo 
 NGSIM    |     HeGA         | [HeGA: Heterogeneous Graph Aggregation Network for Trajectory Prediction in High-Density Traffic](https://doi.org/10.1145/3511808.3557345) |  [Pytorch](https://github.com/GCDAN/GCDAN) 
![Stars](https://img.shields.io/github/stars/GCDAN/GCDAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GCDAN/GCDAN?color=critical&style=social) | CIKM 2022

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2    |     SGTN         | [Social Graph Transformer Networks for Pedestrian Trajectory Prediction in Complex Social Scenarios](https://doi.org/10.1145/3511808.3557455) |  [Pytorch](https://github.com/GCDAN/GCDAN) 
![Stars](https://img.shields.io/github/stars/GCDAN/GCDAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GCDAN/GCDAN?color=critical&style=social) | CIKM 2022

| Location | Gowalla 
 Foursquare 
 WiFi-Trace  |     GCDAN         | [Predicting Human Mobility via Graph Convolutional Dual-attentive Networks](https://dl.acm.org/doi/10.1145/3488560.3498400) |  [Pytorch](https://github.com/GCDAN/GCDAN) 
![Stars](https://img.shields.io/github/stars/GCDAN/GCDAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/GCDAN/GCDAN?color=critical&style=social) | WSDM 2022

| Location | MI 
 SIP   |     CMT-Net         | [CMT-Net: A Mutual Transition Aware Framework for Taxicab Pick-ups and Drop-offs Co-Prediction](https://dl.acm.org/doi/10.1145/3488560.3498394) | None | WSDM 2022

| Location | Gowalla 
 FS-NYC  
 FS-TKY  |     MobTCast       | [MobTCast: Leveraging Auxiliary Trajectory Forecasting for Human Mobility Prediction](https://proceedings.neurips.cc/paper/2021/hash/fecf2c550171d3195c879d115440ae45-Abstract.html) | [Author](https://drive.google.com/drive/folders/1xfiaz9cAxKYmNWgOH986JpMVSQbt3_qu?usp=sharing) | NeurIPS 2021

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2   |     CARPe       | [CARPe Posterum: A Convolutional Approach for Real-Time Pedestrian Path Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/16335) | [Pytorch](https://github.com/TeCSAR-UNCC/CARPe_Posterum) 
![Stars](https://img.shields.io/github/stars/TeCSAR-UNCC/CARPe_Posterum?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/TeCSAR-UNCC/CARPe_Posterum?color=critical&style=social) | AAAI 2021

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2   |     TPNMS       | [Temporal Pyramid Network for Pedestrian Trajectory Prediction with Multi-Supervision](https://ojs.aaai.org/index.php/AAAI/article/view/16299) | [Pytorch](https://github.com/Blessinglrq/TPNMS) 
![Stars](https://img.shields.io/github/stars/Blessinglrq/TPNMS?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Blessinglrq/TPNMS?color=critical&style=social) | AAAI 2021

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2   |     DMRGCN       | [Disentangled Multi-Relational Graph Convolutional Network for Pedestrian Trajectory Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/16174) | [Pytorch](https://github.com/TeCSAR-UNCC/CARPe_Posterum) 
![Stars](https://img.shields.io/github/stars/TeCSAR-UNCC/CARPe_Posterum?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/TeCSAR-UNCC/CARPe_Posterum?color=critical&style=social) | AAAI 2021

| Location | Gowalla 
 Foursquare  |     BSDA       | [Location Predicts You: Location Prediction via Bi-direction Speculation and Dual-level Association](https://www.ijcai.org/proceedings/2021/74) | None | IJCAI 2021

| Location | ETH-UCY 
 Collisions 
  NGsim  
Charges   
 NBA  |     FQA       | [Multi-agent Trajectory Prediction with Fuzzy Query Attention](https://proceedings.neurips.cc/paper/2020/hash/fe87435d12ef7642af67d9bc82a8b3cd-Abstract.html) | [Pytorch](https://github.com/nitinkamra1992/FQA) 
![Stars](https://img.shields.io/github/stars/nitinkamra1992/FQA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/nitinkamra1992/FQA?color=critical&style=social) | NeurIPS 2020

| Location | ETH-UCY 
 Collisions 
  NGsim  
Charges   
 NBA  |     ARNN    | [An Attentional Recurrent Neural Network for Personalized Next Location Recommendation](https://ojs.aaai.org/index.php/AAAI/article/view/5337) |   None  | AAAI 2020

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2  |     MDNLSTM    | [Multimodal Interaction-Aware Trajectory Prediction in Crowded Space](https://ojs.aaai.org/index.php/AAAI/article/view/6874) |   None  | AAAI 2020

| Location | Atlantic|     OMuLeT    | [OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/5444) |   [Matlab](https://github.com/cqwangding/OMuLeT)   | AAAI 2020

| Location | Gowalla 
 Foursquare  |     Flashback  | [OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting](https://www.ijcai.org/Proceedings/2020/302) |  [Pytorch](https://github.com/eXascaleInfolab/Flashback_code)  
![Stars](https://img.shields.io/github/stars/eXascaleInfolab/Flashback_code?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/eXascaleInfolab/Flashback_code?color=critical&style=social) | IJCAI 2020

| Location | CrowdCJ 
 TrashBins  
B&B  
 MYOPIC  |     MALMCS  | [Dynamic Public Resource Allocation Based on Human Mobility Prediction](https://doi.org/10.1145/3380986) |  [Python](https://github.com/sjruan/malmcs)  
![Stars](https://img.shields.io/github/stars/sjruan/malmcs?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sjruan/malmcs?color=critical&style=social) | UbiComp 2020

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2   |     Social-BiGAT  | [Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks](https://proceedings.neurips.cc/paper/2019/hash/d09bf41544a3365a46c9077ebb5e35c3-Abstract.html) |  None  | NeurIPS 2019

| Location | Foursquare 
 Gowalla    |     VANext  | [Predicting Human Mobility via Variational Attention](https://doi.org/10.1145/3308558.3313610) |  None  | WWW 2019

| Location | Flickr 
 Foursquare  
  Geolife  |     CATHI  | [Context-aware Variational Trajectory Encoding and Human Mobility Inference](https://doi.org/10.1145/3308558.3313608) |  None  | WWW 2019

| Location | ETH 
 Hotel  
 Univ 
 Zara1 
 Zara2  |     STGAT  | [STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction](https://openaccess.thecvf.com/content_ICCV_2019/html/Huang_STGAT_Modeling_Spatial-Temporal_Interactions_for_Human_Trajectory_Prediction_ICCV_2019_paper.html) |  [Pytorch](https://github.com/huang-xx/STGAT)  
![Stars](https://img.shields.io/github/stars/huang-xx/STGAT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/huang-xx/STGAT?color=critical&style=social) | ICCV 2019

| Location | BaiduBJ  |     HST-LSTM  | [HST-LSTM: A Hierarchical Spatial-Temporal Long-Short Term Memory Network for Location Prediction](https://www.ijcai.org/proceedings/2018/324) |  [Pytorch](https://github.com/Logan-Lin/ST-LSTM_PyTorch)  
![Stars](https://img.shields.io/github/stars/Logan-Lin/ST-LSTM_PyTorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Logan-Lin/ST-LSTM_PyTorch?color=critical&style=social) | IJCAI 2018

| Location | Foursquare   
 MobileAPP 
 CellularSH |     DeepMove | [DeepMove: Predicting Human Mobility with Attentional Recurrent Networks](https://doi.org/10.1145/3178876.3186058) |  [Pytorch](https://github.com/vonfeng/DeepMove)  
![Stars](https://img.shields.io/github/stars/vonfeng/DeepMove?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/vonfeng/DeepMove?color=critical&style=social) | WWW 2018

| Location |  MORE  |     MORE       | [github](https://github.com/xuehaouwa/Awesome-Trajectory-Prediction) | [Hao Xue](https://github.com/xuehaouwa/Awesome-Trajectory-Prediction) | MORE

| Location |  MORE  |     MORE       | [https://github.com/Pursueee/Trajectory-Paper-Collation](https://github.com/Pursueee/Trajectory-Paper-Collation) | [Pytorch](https://github.com/Pursueee/Trajectory-Paper-Collation) 
![Stars](https://img.shields.io/github/stars/Pursueee/Trajectory-Paper-Collation?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Pursueee/Trajectory-Paper-Collation?color=critical&style=social) | MORE

# [Event Prediction](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums:21 |  |   |   |   |    |

| Event | ETT 
 PM2.5 
 IndD |         NsTKA        | [Non-stationary Time-aware Kernelized Attention for Temporal Event Prediction](https://doi.org/10.1145/3534678.3539470) | [Future](https://github.com/alipay/nstka-kdd22) | KDD 2022

| Crime Prediction | Chicago Crime
 LA Crime
 |         HAGEN     | [HAGEN: Homophily-Aware Graph Convolutional Recurrent Network for Crime Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/20338) | [Pytorch](https://github.com/Rafa-zy/HAGEN) 
![Stars](https://img.shields.io/github/stars/Rafa-zy/HAGEN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Rafa-zy/HAGEN?color=critical&style=social) | AAAI 2022

| Event | PEMS  |         AGWN        | [Early Forecast of Traffc Accident Impact Based on a Single-Snapshot Observation (Student Abstract)](https://aaai-2022.virtualchair.net/poster_sa103) | [Pytorch](https://github.com/gm3g11/AGWN) 
![Stars](https://img.shields.io/github/stars/gm3g11/AGWN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gm3g11/AGWN?color=critical&style=social) | AAAI 2022

| Event  |  SLA-VAE 
 E-commerce  |       RETE    | [RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph](https://doi.org/10.1145/3485447.3511974) | [Pytorch](https://github.com/DiMarzioBian/RETE_TheWebConf) 
![Stars](https://img.shields.io/github/stars/DiMarzioBian/RETE_TheWebConf?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/DiMarzioBian/RETE_TheWebConf?color=critical&style=social) | WWW 2022

| Event | NYC 
 Chicago |         GSNet        | [GSNet: Learning Spatial-Temporal Correlations from Geographical and Semantic Aspects for Traffic Accident Risk Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/16566) | [Pytorch](https://github.com/Echohhhhhh/GSNet) 
![Stars](https://img.shields.io/github/stars/Echohhhhhh/GSNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Echohhhhhh/GSNet?color=critical&style=social) | AAAI 2021

| Event | NYCIncidents 
 CHIIncidents 
  SFIncidents   |     STCGNN       | [Spatio-Temporal-Categorical Graph Neural Networks for Fine-Grained Multi-Incident Co-Prediction](https://doi.org/10.1145/3459637.3482482) | [Pytorch](https://github.com/underdoc-wang/STC-GNN) 
![Stars](https://img.shields.io/github/stars/underdoc-wang/STC-GNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/underdoc-wang/STC-GNN?color=critical&style=social) | CIKM 2021

| Event | Thailand 
 Egypt 
  India  
Russia   
 Covid-19  |     CMF       | [Understanding Event Predictions via Contextualized Multilevel Feature Learning](https://doi.org/10.1145/3459637.3482309) | None  | CIKM 2021

| Event  Prediction  |  DJIA30   
 WebTraffic   
 NetFlow  
 ClockErr  
   AbServe  |        EvoNet    | [Time-Series Event Prediction with Evolutionary State Graph](https://doi.org/10.1145/3437963.3441827) |   [tf](https://github.com/VachelHU/EvoNet)   | WSDM 2021

| Event | NYCIncidents 
 CHIIncidents 
  SFIncidents   |     PreView       | [Dynamic Heterogeneous Graph Neural Network for Real-time Event Prediction](https://doi.org/10.1145/3394486.3403373) | None | KDD 2020

| Event Prediction | MIMIC-III   |      DSSM     | [Deep State-Space Generative Model For Correlated Time-to-Event Predictions](https://doi.org/10.1145/3394486.3403206) | None | KDD 2020

| Event | Beijing 
 Suzhou 
 Shenyang |         RiskOracle        | [RiskOracle: A Minute-Level Citywide Traffic Accident Forecasting Framework](https://ojs.aaai.org//index.php/AAAI/article/view/5480) | [TF](https://github.com/zzyy0929/AAAI2020-RiskOracle/) 
![Stars](https://img.shields.io/github/stars/zzyy0929/AAAI2020-RiskOracle/?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zzyy0929/AAAI2020-RiskOracle/?color=critical&style=social) | AAAI 2020

| Event | NYCIncidents 
 CHIIncidents  |     STrans       | [Hierarchically Structured Transformer Networks for Fine-Grained Spatial Event Forecasting](https://doi.org/10.1145/3366423.3380296) | None  | WWW 2020

| Event | FewEvent  |     DMB-PN       | [Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection](https://dl.acm.org/doi/10.1145/3336191.3371796) | [dataset](https://github.com/231sm/Low_Resource_KBP)  | WSDM 2020

| Event | NYC 
 SIP  |         RiskSeq        | [Foresee Urban Sparse Traffic Accidents: A Spatiotemporal Multi-Granularity Perspective](https://ieeexplore.ieee.org/document/9242313) | None| TKDE 2020

| Event | MemeTracker  
  Weibo  |    LANTERN      | [Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling](https://proceedings.neurips.cc/paper/2019/hash/a29d1598024f9e87beab4b98411d48ce-Abstract.html) | [Pytorch](https://github.com/zhangzx-sjtu/LANTERN-NeurIPS-2019)  
![Stars](https://img.shields.io/github/stars/zhangzx-sjtu/LANTERN-NeurIPS-2019?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhangzx-sjtu/LANTERN-NeurIPS-2019?color=critical&style=social) | NeurIPS 2019

| Event | Graph  
  Stack  
 SmartHome 
 CarIndicators |    WGP-LN, 
  FD-Dir     | [Uncertainty on Asynchronous Time Event Prediction](https://proceedings.neurips.cc/paper/2019/hash/78efce208a5242729d222e7e6e3e565e-Abstract.html) | [TF](https://github.com/sharpenb/Uncertainty-Event-Prediction)  
![Stars](https://img.shields.io/github/stars/sharpenb/Uncertainty-Event-Prediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/sharpenb/Uncertainty-Event-Prediction?color=critical&style=social) | NeurIPS 2019

| Event | Thailand 
 Egypt 
  India  
Russia |    DynamicGCN    | [Learning Dynamic Context Graphs for Predicting Social Events](https://doi.org/10.1145/3292500.3330919) |    [Pytorch](https://github.com/amy-deng/DynamicGCN)  
![Stars](https://img.shields.io/github/stars/amy-deng/DynamicGCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/amy-deng/DynamicGCN?color=critical&style=social) | KDD 2019

| Event | NYCCollision  
  ChicagoCrime  
 NYCTaxi |    DMPP    | [Deep Mixture Point Processes: Spatio-temporal Event Prediction with Rich Contextual Information](https://dl.acm.org/doi/10.1145/3292500.3330937) |    None  | KDD 2019

| Event | Civil 
 Air Quality  |    SIMDA    | [Incomplete Label Multi-Task Deep Learning for Spatio-Temporal Event Subtype Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/4245) |  None  | AAAI 2019

| Crime Prediction  | NYC Crime 
 NYC Anomaly   
  Chicago Crime  |        MiST      | [MiST: A Multiview and Multimodal Spatial-Temporal Learning Framework for Citywide Abnormal Event Forecasting](https://doi.org/10.1145/3308558.3313730) | None  | WWW 2019

| Event | NYCAccident 
 NYCEvent  |    DFN    | [Deep Dynamic Fusion Network for Traffic Accident Forecasting](https://doi.org/10.1145/3357384.3357829) |  None  | CIKM 2019

| Event |   |         Hetero-ConvLSTM        | [Hetero-ConvLSTM: A Deep Learning Approach to Traffic Accident Prediction on Heterogeneous Spatio-Temporal Data](https://ieeexplore.ieee.org/document/9242313) | None| KDD 2018

# [Stock Prediction](#content) 
|  Task  |    Data |   Model  | Paper   | 
| :-: | :-: | :-: | :-: | :-: | - | 
| Paper Nums:30+ |  |   | 
| Stock Price 
 Prediction  | NASDAQ   
 NYSE 
| Stock Price 
 Prediction  |  CSI 300 
| Stock Movement 
 Prediction  | Qin   
 MAEC | 
| Stock Trend 
 Prediction |  CSI 300   
  CSI 500   | 
| Stock Movement 
 Prediction |  ACL18   
  DJIA   | 
| Stock 
 Prediction | NASDAQ   
  NYSE   
 CSI | 
| Stock Movement 
 Prediction | S&P 500 | 
| Stock Price 
 Prediction |  ACL18   | 
| Stock Price 
 Prediction |  CSI 300   
   CSI 500 
| Stock Movement 
 Prediction | Calls | 
| Stock Prediction | NASDAQ 
 NYSE  
  TSE | 
| Stock Prediction | S&P 500 
 Ashare&HK | 
| Stock 
 Prediction | S&P500 
 CSI300 
| Stock 
 Prediction | CSI800 |    PASN 
| Stock Movement
 Prediction | NASDAQ 
 Bitcoin | 
| Stock Movement
 Prediction | CSI800 | 
| Stock Movement 
 Prediction | ACL18 
| Stock  
 Prediction | Self-defined | 
| Stock Selection | NASDAQ  
 NYSE 
 TSE| 
| Stock Movement
 Prediction | TPX500 | 
| Stock Trend
 Prediction |  CSI300 
 SPX 
 
| Stock Movement
 Prediction | NASDAQ 
| Stock Trend
 Prediction |  CSI300 
 CSI500 
| Stock Trend 
 Prediction | CSI300  
 
| Stock Movement 
 Prediction | Self-defined | 
| Stock Movement 
 Prediction | TPX500 
 TPX100 | 
| Stock Movement 
 Prediction | NASDAQ 
 ChinaAShare | 
| Stock Trend
 Prediction |  FI-2010 
 CSI-2016 
| Stock Price 
 Forecasting |  Self-defined | 
| Stock Volatility 
 Forecasting |  Calls | 
| Quantitative 
 Investments  | Self-defined | 
| Stock Price 
 Prediction |  TAQ  | 
| Stock Movement 
 Prediction | HATS | 
| Stock Market 
 Prediction | Nikkei | 
| Stock Trend 
 Prediction |  ChineseStock | 
| Stock Movement 
 Prediction | CSI200 
 CSI300 
| Stock Movement 
 Prediction | Self-defined | 
| Stock Movement 
 Prediction | ACL18 
| Stock  Prediction | NASDAQ  
 NYSE  | 
| Stock Movement 
 Prediction | Self-defined  | 
| Stock Trend 
 Prediction | Self-defined  | 
| Stock Price 
 Prediction | Self-defined | 
| Stock Movement 
 Prediction | NASDAQ  
 NYSE  |

Code    |   Publication    | |   |    | 
 S&P500  |         StockMixer      | [StockMixer: A Simple Yet Strong MLP-Based Architecture for Stock Price Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/28681) | [Pytorch](https://github.com/SJTU-Quant/StockMixer) 
![Stars](https://img.shields.io/github/stars/SJTU-Quant/StockMixer?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SJTU-Quant/StockMixer?color=critical&style=social) | AAAI 2024 
  CSI 800   |         MASTER      | [MASTER: Market-Guided Stock Transformer for Stock Price Forecasting](https://ojs.aaai.org/index.php/AAAI/article/view/27767) | [Pytorch](https://github.com/SJTU-Quant/MASTER) 
![Stars](https://img.shields.io/github/stars/SJTU-Quant/MASTER?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SJTU-Quant/MASTER?color=critical&style=social) | AAAI 2024 ECHO-GL      | [ECHO-GL: Earnings Calls-Driven Heterogeneous Graph Learning for Stock Movement Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/29305) | [Pytorch](https://github.com/pupu0302/ECHOGL) 
![Stars](https://img.shields.io/github/stars/pupu0302/ECHOGL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/pupu0302/ECHOGL?color=critical&style=social) | AAAI 2024 DoubleAdapt      | [DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting](https://doi.org/10.1145/3580305.3599315) | [Pytorch](https://github.com/SJTU-Quant/DoubleAdapt) 
![Stars](https://img.shields.io/github/stars/SJTU-Quant/DoubleAdapt?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SJTU-Quant/DoubleAdapt?color=critical&style=social) | KDD 2023 PEN      | [PEN: Prediction-Explanation Network to Forecast Stock Price Movement with Better Explainability](https://ojs.aaai.org/index.php/AAAI/article/view/25648) | [TF](https://github.com/Shuqi-li/PEN) 
![Stars](https://img.shields.io/github/stars/Shuqi-li/PEN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Shuqi-li/PEN?color=critical&style=social) | AAAI 2023 RT-GCN      | [Relational Temporal Graph Convolutional Networks for Ranking-Based Stock Prediction](https://ieeexplore.ieee.org/document/10184655) | [Pytorch](https://github.com/zhengzetao/RTGCN) 
![Stars](https://img.shields.io/github/stars/zhengzetao/RTGCNt?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/zhengzetao/RTGCN?color=critical&style=social) | ICDE 2023 ESTIMATE      | [Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction](https://doi.org/10.1145/3539597.3570427) | [Pytorch](https://github.com/thanhtrunghuynh93/estimate) 
![Stars](https://img.shields.io/github/stars/thanhtrunghuynh93/estimate?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/thanhtrunghuynh93/estimate?color=critical&style=social) | WSDM 2023 D-va      | [Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction](https://dl.acm.org/doi/10.1145/3583780.3614844) | [Gluonts](https://github.com/koa-fin/dva) 
![Stars](https://img.shields.io/github/stars/koa-fin/dva?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/koa-fin/dva?color=critical&style=social) | CIKM 2023 
  CSI 800     |       CISP     | [Follow the Will of the Market: A Context-Informed Drift-Aware Method for Stock Prediction](https://dl.acm.org/doi/10.1145/3583780.3614886) | None  | CIKM 2023 NumHTML      | [NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-task Financial Forecasting](https://aaai-2022.virtualchair.net/poster_aaai4799) | [Future,Author](https://github.com/YangLinyi) | AAAI 2022 ALSP-TF      | [Adaptive Long-Short Pattern Transformer for Stock Investment Selection](https://doi.org/10.24963/ijcai.2022/551) | None | IJCAI 2022 HISN     | [Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation](https://doi.org/10.24963/ijcai.2022/550) | None | IJCAI 2022 
 Twitter |    THGNN  | [Temporal and Heterogeneous Graph Neural Network for Financial Time Series Prediction](https://doi.org/10.1145/3511808.3557089) | None | CIKM 2022 | [Pattern Adaptive Specialist Network for Learning Trading Patterns in Stock Market](https://doi.org/10.1145/3511808.3557665) | None | CIKM 2022 KHIT  | [Kernel-based Hybrid Interpretable Transformer for High-frequency Stock Movement Prediction](https://ieeexplore.ieee.org/document/10027785) | None | ICDM 2022 TRA  |   [Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport](https://doi.org/10.1145/3447548.3467358) | [Pytorch](https://github.com/microsoft/qlib/tree/main/examples/benchmarks/TRA) 
![Stars](https://img.shields.io/github/stars/microsoft/qlib/tree/main/examples/benchmarks/TRA?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/microsoft/qlib/tree/main/examples/benchmarks/TRA?color=critical&style=social) | KDD 2021 
 KDD17 
 NDX100  
 CSI300  
 NI225
 FTSE100 |     DTML | [Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts](https://doi.org/10.1145/3447548.3467297) | None| KDD 2021 AD-GAT | [Modeling the Momentum Spillover Effect for Stock Prediction via Attribute-Driven Graph Attention Networks](https://ojs.aaai.org/index.php/AAAI/article/view/16077) | [Pytorch](https://github.com/RuichengFIC/ADGAT) 
![Stars](https://img.shields.io/github/stars/RuichengFIC/ADGAT?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/RuichengFIC/ADGAT?color=critical&style=social) | AAAI 2021 STHAN-SR        | [Stock Selection via Spatiotemporal Hypergraph Attention Network: A Learning to Rank Approach](https://ojs.aaai.org/index.php/AAAI/article/view/16127) | None | AAAI 2021 CGM  |   [Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling](https://www.ijcai.org/proceedings/2021/0518.pdf) | [Pytorch](https://github.com/lancopku/CGM) 
![Stars](https://img.shields.io/github/stars/lancopku/CGM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/lancopku/CGM?color=critical&style=social) | IJCAI 2021 TOPIX-100   |    HATR  |   [Hierarchical Adaptive Temporal-Relational Modeling for Stock Trend Prediction](https://www.ijcai.org/proceedings/2021/0508.pdf) |  None  | IJCAI 2021 
 NYSE 
 TSE 
 China & HK |    HyperStockGAT  |   [Learning Multiple Stock Trading Patterns with Temporal Routing Adaptor and Optimal Transport](https://doi.org/10.1145/3442381.3450095) | None| WWW 2021 |    REST  |   [REST: Relational Event-driven Stock Trend Forecasting](https://doi.org/10.1145/3442381.3450032) | None | WWW 2021 CSI800 
 NASDAQ100|        CMLF       | [Stock Trend Prediction with Multi-granularity Data: A Contrastive Learning Approach with Adaptive Fusion](https://doi.org/10.1145/3459637.3482483) | [Pytorch](https://github.com/CMLF-git-dev/CMLF)  
![Stars](https://img.shields.io/github/stars/CMLF-git-dev/CMLF?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CMLF-git-dev/CMLF?color=critical&style=social) | CIKM 2021 MFN  | [Incorporating Expert-Based Investment Opinion Signals in Stock Prediction: A Deep Learning Framework](https://ojs.aaai.org/index.php/AAAI/article/view/5445) | None | AAAI 2020 LSTM-RGCN | [Modeling the Stock Relation with Graph Network for Overnight Stock Movement Prediction](https://www.ijcai.org/proceedings/2020/0626.pdf) | [Pytorch](https://github.com/liweitj47/overnight-stock-movement-prediction) 
![Stars](https://img.shields.io/github/stars/liweitj47/overnight-stock-movement-prediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/liweitj47/overnight-stock-movement-prediction?color=critical&style=social) | IJCAI 2020 HMG-TF | [Hierarchical Multi-Scale Gaussian Transformer for Stock Movement Prediction](https://www.ijcai.org/proceedings/2020/0640.pdf) | None | IJCAI 2020 |    MTDNN  |   [Multi-scale Two-way Deep Neural Network for Stock Trend Prediction](https://www.ijcai.org/proceedings/2020/0628.pdf) | [Future](https://github.com/marscrazy/MTDNN) | IJCAI 2020 Dandelion       | [Domain adaptive multi-modality neural attention network for financial forecasting](https://doi.org/10.1145/3366423.3380288) | [Sklearn](https://github.com/Leo02016/Dandelion)  | WWW 2020 HTML       | [Hierarchical Transformer-based Multi-task Learning for Volatility Prediction](https://doi.org/10.1145/3366423.3380128) | [Pytorch](https://github.com/YangLinyi/HTML-Hierarchical-Transformer-based-Multi-task-Learning-for-Volatility-Prediction)  
![Stars](https://img.shields.io/github/stars/YangLinyi/HTML-Hierarchical-Transformer-based-Multi-task-Learning-for-Volatility-Prediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/YangLinyi/HTML-Hierarchical-Transformer-based-Multi-task-Learning-for-Volatility-Prediction?color=critical&style=social) | WWW 2020 KGEEF  | [Knowledge Graph-based Event Embedding Framework for Financial Quantitative Investments](https://doi.org/10.1145/3397271.3401427) | None | SIGIR 2020 GARCH-LSTM  | [Price Forecast with High-Frequency Finance Data: An Autoregressive Recurrent Neural Network Model with Technical Indicators](https://doi.org/10.1145/3340531.3412738) |  None   | CIKM 2020 STHGCN       | [Spatiotemporal hypergraph convolution network for stock movement forecasting](https://ieeexplore.ieee.org/abstract/document/9338303) | [Pytorch](https://github.com/midas-research/sthgcn-icdm) 
![Stars](https://img.shields.io/github/stars/midas-research/sthgcn-icdm?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/midas-research/sthgcn-icdm?color=critical&style=social) | ICDM 2020 GNNs  | [Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis](https://arxiv.org/abs/1909.10660) | None | NeurIPSw 2019 IMTR       | [Investment Behaviors Can Tell What Inside: Exploring Stock Intrinsic Properties for Stock Trend Prediction](https://doi.org/10.1145/3292500.3330663) | None| KDD 2019 
 CSI500 |         RNN-MRFs  | [Multi-task Recurrent Neural Networks and Higher-order Markov Random Fields for Stock Price Movement Prediction: Multi-task RNN and Higer-order MRFs for Stock Price Classification](https://doi.org/10.1145/3292500.3330983) | None | KDD 2019 TTIO  | [Individualized Indicator for All: Stock-wise Technical Indicator Optimization with Stock Embedding](https://doi.org/10.1145/3292500.3330833) | None | KDD 2019 
 KDD17 
 NDX100  
 CSI300  
 NI225
 FTSE100|         Adv-ALSTM  | [Enhancing stock movement prediction with adversarial training](https://www.ijcai.org/proceedings/2019/0810.pdf) | [TF](https://github.com/fulifeng/Adv-ALSTM) 
![Stars](https://img.shields.io/github/stars/fulifeng/Adv-ALSTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/fulifeng/Adv-ALSTM?color=critical&style=social) | IJCAI 2019 RSR  | [Temporal Relational Ranking for Stock Prediction](https://doi.org/10.1145/3292500.3330833) | [TF](https://github.com/fulifeng/Temporal_Relational_Stock_Ranking) 
![Stars](https://img.shields.io/github/stars/fulifeng/Temporal_Relational_Stock_Ranking?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/fulifeng/Temporal_Relational_Stock_Ranking?color=critical&style=social) | TOIS 2019 StockNet   | [Stock Movement Prediction from Tweets and Historical Prices](https://aclanthology.org/P18-1183) | [TF](https://github.com/yumoxu/stocknet-code) 
![Stars](https://img.shields.io/github/stars/yumoxu/stocknet-code?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yumoxu/stocknet-code?color=critical&style=social) | ACL 2018 HAN  | [Listening to Chaotic Whispers: A Deep Learning Framework for News-oriented Stock Trend Prediction](https://doi.org/10.1145/3159652.3159690) | [TF](https://github.com/donghyeonk/han) 
![Stars](https://img.shields.io/github/stars/donghyeonk/han?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/donghyeonk/han?color=critical&style=social) | WSDM 2018 SFM  | [Stock Price Prediction via Discovering Multi-Frequency Trading Patterns](https://doi.org/10.1145/3097983.3098117) | [Keras](https://github.com/z331565360/State-Frequency-Memory-stock-prediction) 
![Stars](https://img.shields.io/github/stars/z331565360/State-Frequency-Memory-stock-prediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/z331565360/State-Frequency-Memory-stock-prediction?color=critical&style=social) | KDD 2017 KGEB-CNN   | [Knowledge-Driven Event Embedding for Stock Prediction](https://aclanthology.org/C16-1201) | None | COLING 2016

# [Other Forecasting](#content)

|  Task  |    Data |   Model  | Paper   |    Code    |   Publication    |

| :-: | :-: | :-: | :-: | :-: | - |

| Paper Nums:40+ |  |   |   |   |    |

| Water Temperature   
 Prediction  | Delaware  
 River Basin  |        SR-MTL    | [Meta-Transfer-Learning for Time Series Data with Extreme Events: An Application to Water Temperature Prediction](https://dl.acm.org/doi/abs/10.1145/3583780.3614966) |     None  | CIKM 2023

| Telecommunication  
 Traffic  
 Forecasting  | Milan (MI) 
 Trentino (TN) |        TMLM    | [Telecommunication Traffic Forecasting via Multi-task Learning](https://doi.org/10.1145/3539597.3570440) |     [Author](https://github.com/gpxlcj)   | WSDM 2022

| Bitcoin   
 Volatility  
 Forecasting  | Twitter |        D-TCN	    | [Ask "Who", Not "What": Bitcoin Volatility Forecasting with Twitter Data](https://doi.org/10.1145/3539597.3570387) |     [TF](https://github.com/meakbiyik/ask-who-not-what)   
![Stars](https://img.shields.io/github/stars/meakbiyik/ask-who-not-what?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/meakbiyik/ask-who-not-what?color=critical&style=social) | WSDM 2022

| Rating 
  Migration  
 Prediction |  Self |      META      | [Multi-task Envisioning Transformer-based Autoencoder for Corporate Credit Rating Migration Early Prediction](https://doi.org/10.1145/3534678.3539098) | None | KDD 2022

| COVID-19 
 Prediction | TokyoCOVID19  |        SAB-GNN       | [Multiwave COVID-19 Prediction from Social Awareness Using Web Search and Mobility Data](https://doi.org/10.1145/3534678.3539172) | [Pytorch](https://github.com/JiaweiXue/MultiwaveCovidPrediction) 
![Stars](https://img.shields.io/github/stars/JiaweiXue/MultiwaveCovidPrediction?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/JiaweiXue/MultiwaveCovidPrediction?color=critical&style=social) | KDD 2022

| Service  
 Time 
 Prediction | DowBJ  
 SubBJ |        MetaSTP       | [Service Time Prediction for Delivery Tasks via Spatial Meta-Learning](https://doi.org/10.1145/3534678.3539027) | None | KDD 2022

| Physician 
 Burnout 
 Prediction | EHR  
 Burnout |        HiPAL       | [HiPAL: A Deep Framework for Physician Burnout Prediction Using Activity Logs in Electronic Health Records](https://doi.org/10.1145/3534678.3539056) | [TF](https://github.com/HanyangLiu/HiPAL)  
![Stars](https://img.shields.io/github/stars/HanyangLiu/HiPAL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HanyangLiu/HiPAL?color=critical&style=social) | KDD 2022

| Crop Yield  Prediction | American Crop |         GNN-RNN        | [A GNN-RNN Approach for Harnessing Geospatial and Temporal Information: Application to Crop Yield Prediction](https://aaai-2022.virtualchair.net/poster_aisi6416) | None  | AAAI 2022

| Epidemic Prediction | Globe 
 US-State  
 US-County |         CausalGNN     | [CausalGNN: Causal-based Graph Neural Networks for Spatio-Temporal](https://aaai-2022.virtualchair.net/poster_aisi6475) | Future | AAAI 2022

| Soil Moisture 
 Forecasting | Spain 
 USA |         DGLR     | [Dynamic Structure Learning through Graph Neural Network for Forecasting Soil Moisture in Precision Agriculture](https://doi.org/10.24963/ijcai.2022/720) | [Pytorch](https://github.com/AnoushkaVyas/DGLR)  
![Stars](https://img.shields.io/github/stars/AnoushkaVyas/DGLR?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AnoushkaVyas/DGLR?color=critical&style=social) | IJCAI 2022

| Disease Prediction | Disease 
 Tumors   |         PopNet     | [PopNet: Real-Time Population-Level Disease Prediction with Data Latency](https://doi.org/10.1145/3485447.3512127) | [Pytorch](https://github.com/v1xerunt/PopNet) 
![Stars](https://img.shields.io/github/stars/v1xerunt/PopNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/v1xerunt/PopNet?color=critical&style=social) | WWW 2022

| FakeNews Detection | Snop 
 PolitiFact  |         GET     | [Evidence-aware Fake News Detection with Graph Neural Networks](https://doi.org/10.1145/3485447.3512122) | [Keras](https://github.com/CRIPAC-DIG/GET) 
![Stars](https://img.shields.io/github/stars/CRIPAC-DIG/GET?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CRIPAC-DIG/GET?color=critical&style=social) | WWW 2022

| Crime Prediction | NYC 
 Chicago |         ST-HSL     | [Spatial-Temporal Hypergraph Self-Supervised Learning for Crime Prediction](https://ieeexplore.ieee.org/document/9835423) | [Pytorch](https://github.com/LZH-YS1998/STHSL) 
![Stars](https://img.shields.io/github/stars/LZH-YS1998/STHSL?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/LZH-YS1998/STHSL?color=critical&style=social) | ICDE 2022

| Popularity 
 Prediction | WbTopic 
 WbRepost  
 Twitter |      HERI-GCN    | [Deep Popularity Prediction in Multi-Source Cascade with HERI-GCN](https://ieeexplore.ieee.org/document/9835455) | [Pytorch](https://github.com/Les1ie/HERI-GCN) 
![Stars](https://img.shields.io/github/stars/Les1ie/HERI-GCN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Les1ie/HERI-GCN?color=critical&style=social) | ICDE 2022

|  Parking Pricing | SFMTA 
 SDOT   |      None   | [Prediction-based One-shot Dynamic Parking Pricing](https://doi.org/10.1145/3511808.3557421) | None| CIKM 2022

|   Future Citation   | APS 
 AMiner   |      DGNI   | [Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction](https://doi.org/10.1145/3511808.3557398) | None| CIKM 2022

|   Pandemic  Forecasting  |  Large-MG    |      HiSTGNN   | [Hierarchical Spatio-Temporal Graph Neural Networks for Pandemic Forecasting](https://doi.org/10.1145/3511808.3557350) | None| CIKM 2022

|   Search Traffic 
 Forecasting  |  M5 
 FGSF 
  SQTE |      STARDOM   | [STARDOM: Semantic Aware Deep Hierarchical Forecasting Model for Search Traffic Prediction](https://doi.org/10.1145/3511808.3557102) | None| CIKM 2022

|  Crime Prediction  |   NYC 
 Chicago |      LTFMs   | [Locality Aware Temporal FMs for Crime Prediction](https://doi.org/10.1145/3511808.3557657) | None| CIKM 2022

| Energy Markets |  Nordpool |      None   | [A Graph-based Spatiotemporal Model for Energy Markets](https://doi.org/10.1145/3511808.3557530) | None| CIKM 2022

| Denoised Health 
 Risk Prediction | EHR |    MedSkim  | [MedSkim: Denoised Health Risk Prediction via Skimming Medical Claims Data](https://ieeexplore.ieee.org/document/10027678) | [Pytorch](https://github.com/SH-Src/MedSkim) 
![Stars](https://img.shields.io/github/stars/SH-Src/MedSkim?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/SH-Src/MedSkim?color=critical&style=social) | ICDM 2022

| Demand 
 Prediction | E-Commerce 
 M5 |    Forchestra  | [A Large-Scale Ensemble Learning Framework for Demand Forecasting](https://ieeexplore.ieee.org/document/10027662) | [Pytorch](https://github.com/young-j-park/22-ICDM-Forchestra) 
![Stars](https://img.shields.io/github/stars/young-j-park/22-ICDM-Forchestra?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/young-j-park/22-ICDM-Forchestra?color=critical&style=social) | ICDM 2022

| Transfer 
  Traffic Flow 
 Prediction | ShanghaiBIKE 
 NanjingBus 
 HaikouDiDi |    CCMHC  | [Exploiting Hierarchical Correlations for Cross-City Cross-Mode Traffic Flow Prediction](https://ieeexplore.ieee.org/document/10027729) | [Pytorch](https://github.com/chenyan89/CCMHC) 
![Stars](https://img.shields.io/github/stars/chenyan89/CCMHC?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/chenyan89/CCMHC?color=critical&style=social) | ICDM 2022

| Precipitation  
 Nowcasting | ERA5 
 WeatherBench |    SCC-ConvLSTM  | [Spatiotemporal Contextual Consistency Network for Precipitation Nowcasting](https://ieeexplore.ieee.org/document/10027644) | [Future](https://github.com/EricKing19/SCCN) | ICDM 2022

| Transfer 
  Traffic Flow 
 Prediction | Shenzhen 
 HB 
 Chengdu 
 Xian |    Mest-GAN  | [Mest-GAN: Cross-City Urban Traffic Estimation with Meta Spatial-Temporal Generative Adversarial Networks](https://ieeexplore.ieee.org/document/10027789) | None  | ICDM 2022

| Transfer 
  Human Mobility 
 Prediction | Houston 
 Iowa City |   STORM-GAN | [STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19](https://ieeexplore.ieee.org/document/10027783) | [Pytorch](https://github.com/BaoHan88/STROM-GAN) 
![Stars](https://img.shields.io/github/stars/BaoHan88/STROM-GAN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/BaoHan88/STROM-GAN?color=critical&style=social) | ICDM 2022

| Transfer 
  Traffic Flow 
 Prediction |  Shenzhen 
 HB 
 Chengdu 
 Xian |  STrans-GAN | [STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation](https://ieeexplore.ieee.org/document/10027643) | None | ICDM 2022

| Churn Prediction | Beidian 
 Epinions  |        CFChurn    | [A Counterfactual Modeling Framework for Churn Prediction](https://doi.org/10.1145/3488560.3498468) |     [Pytorch](https://github.com/tsinghua-fib-lab/CFChurn)   
![Stars](https://img.shields.io/github/stars/tsinghua-fib-lab/CFChurn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/tsinghua-fib-lab/CFChurn?color=critical&style=social) | WSDM 2022

| Streaming 
 Traffic Flow  | PEMS03    |         TrafficStream     | [TrafficStream: A Streaming Traffic Flow Forecasting Framework Based on Graph Neural Networks and Continual Learning](https://www.ijcai.org/proceedings/2021/498/) | [Pytorch](https://github.com/AprLie/TrafficStream) 
![Stars](https://img.shields.io/github/stars/AprLie/TrafficStream?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/AprLie/TrafficStream?color=critical&style=social) | IJCAI 2021

| Crime 
 Prediction | NYC 
 Chicago  |         ST-SHN     | [Spatial-Temporal Sequential Hypergraph Network for Crime Prediction with Dynamic Multiplex Relation Learning](https://www.ijcai.org/proceedings/2021/0225.pdf) |     [TF](https://github.com/akaxlh/ST-SHN)   
![Stars](https://img.shields.io/github/stars/akaxlh/ST-SHN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/akaxlh/ST-SHN?color=critical&style=social) | IJCAI 2021

| Purchase Intent Forecasting | JD-e-commerce   |      CHTR          | [Purchase Intent Forecasting with Convolutional Hierarchical Transformer Networks](https://ieeexplore.ieee.org/abstract/document/9458836) | None | ICDE 2021

|  Popularity Prediction  | Tmall   |      ATNN          | [Adversarial Two-Tower Neural Network for New Item’s Popularity Prediction in E-commerce](https://ieeexplore.ieee.org/document/9458869) | None | ICDE 2021

| Career Trajectory Prediction  | Company  
 Position   |      TACTP          | [Variable Interval Time Sequence Modeling for Career Trajectory Prediction: Deep Collaborative Perspective](https://dl.acm.org/doi/10.1145/3442381.3449959) | None | WWW 2021

| Health Prediction | NASH 
 AD  |        UNITE    | [UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data](https://doi.org/10.1145/3442381.3450087) |     [Pytorch](https://github.com/Chacha-Chen/UNITE)   
![Stars](https://img.shields.io/github/stars/Chacha-Chen/UNITE?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Chacha-Chen/UNITE?color=critical&style=social) | WWW 2021

| COVID-19 Forecasting  | JHUCSSE     |         HierST     | [HierST: A Unified Hierarchical Spatial-temporal Framework for COVID-19 Trend Forecasting](https://doi.org/10.1145/3459637.3481927) | [Pytorch](https://github.com/dolphin-zs/HierST) 
![Stars](https://img.shields.io/github/stars/dolphin-zs/HierST?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/dolphin-zs/HierST?color=critical&style=social) | CIKM 2021

| Failure Prediction  | Water Pipe 
 Sewer Pipe    |         FP     | [Failure Prediction for Large-scale Water Pipe Networks Using GNN and Temporal Failure Series](https://doi.org/10.1145/3459637.3481918) | None | CIKM 2021

| Publication Prediction  | CSJ  
 CSC    |         VPALG     | [VPALG: Paper-publication Prediction with Graph Neural Networks](https://doi.org/10.1145/3459637.3482490) | None | CIKM 2021

| Water Quality Prediction  |      |   PDE-DGN    | [Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature](https://ieeexplore.ieee.org/abstract/document/9679188) |  None | ICDM 2021

| Risk Prediction | COPD  
 HeartFailure 
 KidneyDiseases  |      HiTANet     | [HiTANet: Hierarchical Time-Aware Attention Networks for Risk Prediction on Electronic Health Records](https://doi.org/10.1145/3394486.3403107) |  [Pytorch](https://github.com/HiTANet2020/HiTANet)  
![Stars](https://img.shields.io/github/stars/HiTANet2020/HiTANet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HiTANet2020/HiTANet?color=critical&style=social) | KDD 2020

| Sales Prediction | anonymized   |      CARNN     | [Attention based Multi-Modal New Product Sales Time-series Forecasting](https://doi.org/10.1145/3394486.3403362) |  [Pytorch](https://github.com/HumaticsLAB/AttentionBasedMultiModalRNN)  
![Stars](https://img.shields.io/github/stars/HumaticsLAB/AttentionBasedMultiModalRNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/HumaticsLAB/AttentionBasedMultiModalRNN?color=critical&style=social) | KDD 2020

| Economy Prediction | IRS   |        AMCN     | [Attentional Multi-graph Convolutional Network for Regional Economy Prediction with Open Migration Data](https://doi.org/10.1145/3394486.3403273) | None | KDD 2020

| Food Demand | Ele.me   |      OFCT     | [Order Fulfillment Cycle Time Estimation for On-Demand Food Delivery](https://doi.org/10.1145/3394486.3403307) |  None | KDD 2020

| Parking Prediction | Beijing 
 Shanghai |         SHARE       | [Semi-Supervised Hierarchical Recurrent Graph Neural Network for City-Wide Parking Availability Prediction](https://ojs.aaai.org/index.php/AAAI/article/view/5471) |  [Pytorch](https://github.com/Vvrep/SHARE-parking_availability_prediction-Pytorch)  
![Stars](https://img.shields.io/github/stars/Vvrep/SHARE-parking_availability_prediction-Pytorch?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/Vvrep/SHARE-parking_availability_prediction-Pytorch?color=critical&style=social) | AAAI 2020

| Mortality Risk Prediction|  MIMIC-III  
 eICU    |      DATA-GRU     | [DATA-GRU: Dual-Attention Time-Aware Gated Recurrent Unit for Irregular Multivariate Time Series](https://ojs.aaai.org/index.php/AAAI/article/view/5440) |  None | AAAI 2020

| Parking Prediction | Ningbo 
 Changsha |         PewLSTM       | [PewLSTM: Periodic LSTM with Weather-Aware Gating Mechanism for Parking Behavior Prediction](https://www.ijcai.org/proceedings/2020/610) |  [Pytorch](https://github.com/NingxuanFeng/PewLSTM)  
![Stars](https://img.shields.io/github/stars/NingxuanFeng/PewLSTM?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/NingxuanFeng/PewLSTM?color=critical&style=social) | IJCAI 2020

|  Health Risk  Prediction  |  MIMIC-III  
   ESRD |     StageNet      | [StageNet: Stage-Aware Neural Networks for Health Risk Prediction](https://doi.org/10.1145/3366423.3380136) |  [Pytorch](https://github.com/v1xerunt/StageNet)  
![Stars](https://img.shields.io/github/stars/v1xerunt/StageNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/v1xerunt/StageNet?color=critical&style=social) | WWW 2020

|  Micro-video Popularity Prediction  |  Xigua    |      MMVED     | [A Multimodal Variational Encoder-Decoder Framework for Micro-video Popularity Prediction](https://doi.org/10.1145/3366423.3380004) |  [TF](https://github.com/yaochenzhu/MMVED)  
![Stars](https://img.shields.io/github/stars/yaochenzhu/MMVED?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/yaochenzhu/MMVED?color=critical&style=social) | WWW 2020

|  Drug Demand Prediction  |  Wikipedia    |           | [Predicting Drug Demand with Wikipedia Views: Evidence from Darknet Markets](https://doi.org/10.1145/3366423.3380022) |  None  | WWW 2020

|  Epidemic  Prediction  | IDWR 
 CDC 
 US-HHS |     Cola-GNN      | [Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction](https://doi.org/10.1145/3340531.3411975) |  [Pytorch](https://github.com/amy-deng/colagnn)  
![Stars](https://img.shields.io/github/stars/amy-deng/colagnn?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/amy-deng/colagnn?color=critical&style=social) | CIKM 2020

|  Risk  Prediction  | HeartFailure 
 KidneyDisease 
 Dementia |    LSAN    | [LSAN: Modeling Long-term Dependencies and Short-term Correlations with Hierarchical Attention for Risk Prediction](https://doi.org/10.1145/3340531.3411864) |  [Pytorch](https://github.com/dmmlprojs/lsan)  
![Stars](https://img.shields.io/github/stars/dmmlprojs/lsan?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/dmmlprojs/lsan?color=critical&style=social) | CIKM 2020

|  Lightning  Prediction  | Lightning |    HSTN    | [A Heterogeneous Spatiotemporal Network for Lightning Prediction](https://ieeexplore.ieee.org/abstract/document/9338411) |  [Future](https://github.com/gyla1993/HSTN)  | ICDM 2020

|  Disease  Prediction  | mPower  |    RNNODE    | [Predicting Parkinson’s Disease with Multimodal Irregularly Collected Longitudinal Smartphone Data](https://ieeexplore.ieee.org/abstract/document/9338417) | None  | ICDM 2020

|  Turbulence  Prediction  | Turbulence |    T^2-Net    | [T^2-Net: A Semi-Supervised Deep Model for Turbulence Forecasting](https://ieeexplore.ieee.org/document/9338418) | None | ICDM 2020

|  Popularity  Prediction  | Sina Weibo |   CoupledGNN   | [Popularity Prediction on Social Platforms with Coupled Graph Neural Networks](https://doi.org/10.1145/3336191.3371834) |  [TF](https://github.com/CaoQi92/CoupledGNN)  
![Stars](https://img.shields.io/github/stars/CaoQi92/CoupledGNN?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/CaoQi92/CoupledGNN?color=critical&style=social) | WSDM 2020

|  Job Mobility  Prediction  | Self  |   HCPNN   | [A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction](https://doi.org/10.1145/3292500.3330969) |  [Python](https://github.com/qingxin-meng/hierarchical-career-path-aware-network)  
![Stars](https://img.shields.io/github/stars/qingxin-meng/hierarchical-career-path-aware-network?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/qingxin-meng/hierarchical-career-path-aware-network?color=critical&style=social) | KDD 2019

|  Lightning  Prediction  | Lightning  |   LightNet   | [LightNet: A Dual Spatiotemporal Encoder Network Model for Lightning Prediction](https://doi.org/10.1145/3292500.3330717) |  [Keras](https://github.com/gyla1993/LightNet)  
![Stars](https://img.shields.io/github/stars/gyla1993/LightNet?color=critical&style=social) 
![Forks](https://img.shields.io/github/forks/gyla1993/LightNet?color=critical&style=social) | KDD 2019

|  Diagnosis  Prediction  | MIMICIII  |   MNN   | [MNN: Multimodal Attentional Neural Networks for Diagnosis Prediction](https://www.ijcai.org/Proceedings/2019/823) |  None  | IJCAI 2019

|  Crime  Prediction  | CrimeCHI  
  CrimeNYC |   NN-CCRF   | [Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction](https://www.ijcai.org/proceedings/2019/577) | None  | IJCAI 2019

| Talent Flow  Forecasting  |  OPNs   |   ETF    | [Large-Scale Talent Flow Forecast with Dynamic Latent Factor Model?](https://doi.org/10.1145/3308558.3313525) | None | WWW 2019

|  Sales  Prediction  | Snack  
  PG&U |  DSF  | [A Deep Neural Framework for Sales Forecasting in E-Commerce](https://doi.org/10.1145/3357384.3357883) |  None  | CIKM 2019

|  Load  Prediction  | Charging  Stations |  HCFN  | [Heterogeneous Components Fusion Network for Load Forecasting of Charging Stations](https://doi.org/10.1145/3357384.3358073) |  None  | CIKM 2019

|  Mortality Risk  Prediction  | PUB  
 MIMIC-III |     UA-CRNN     | [UA-CRNN: Uncertainty-Aware Convolutional Recurrent Neural Network for Mortality Risk Prediction](https://doi.org/10.1145/3357384.3357884) |  None | CIKM 2019

|  House Price  Prediction  | NYCHouse  
 BJHouse |    FTD_DenseNet    | [An Integrated Model for Urban Subregion House Price Forecasting: A Multi-source Data Perspective](https://ieeexplore.ieee.org/abstract/document/8970751) |  None  | ICDM 2019

|  Water Quality Prediction  |   |   TC    | [Predicting Water Quality for the Woronora Delivery Network with Sparse Samples](https://ieeexplore.ieee.org/abstract/document/8970721) | None  | ICDM 2019

# [Conferences](#content)

❗ It is highly recommended to utilize [dblp](https://dblp.uni-trier.de/) and [Aminer](https://www.aminer.cn/conf) (in Chinese) to search.

Some more useful websites:

- CCF conference deadlines: https://ccfddl.github.io/

- Conference eye (会议之眼): https://www.conferenceeye.cn/#/layout/home

- Call4Papers: http://123.57.137.208/ccf/ccf-8.jsp

- Conference list: http://www.conferencelist.info/upcoming.html

- PMLR: https://proceedings.mlr.press/    （contains ICML, AISTATS, ACML, UAI, etc）

## Table of Conferences

|Conference | Approximate submission time |

|:--|:--|

| [IJCAI](#IJCAI)    | 1.14\~2.15 |

| [ICML](#ICML)      | 1.23\~2.24 |

| [KDD](#KDD)        | 2.3\~2.17  |

| [CIKM](#CIKM)      | 5.15\~5.26 |

| [NeurIPS](#NeurIPS)| 5.18\~6.5  |

| [ICDM](#ICDM)      | 6.5\~6.17  |

| [WSDM](#WSDM)      | 7.17\~8.16 |

| [AAAI](#AAAI)      | 9.5\~9.15  |

| [ICLR](#ICLR)      | 9.25\~10.27|

| [WWW](#WWW)        | 10.14\~11.5|

| [ICDE-1](#ICDE)    | 6.1\~7.21  |

| [ICDE-2](#ICDE)    | 10.1\~11.17|

Approximate conference submission times from the most recent 7 years.

## Conference (Journal) CCF Ranks

|Conference (Journal) | CCF Rank |

|:--|:--|

| ICML         | A            |

| NeurIPS      | A            |  

| ICLR         | None but top |

| KDD          | A            |  

| AAAI         | A            |

| IJCAI        | A            |  

| ICDE         | A            |

| WWW          | A            |

| ACL          | A            |

| INFOCOM      | A            |

| SIGIR        | A            |

| VLDB         | A            |

| UbiComp      | A            |

| TKDE         | A            |

| TPAMI        | A            |

| TOIS         | A            |

| CIKM         | B            |

| ICDM         | B            |

| WSDM         | B            |

| COLING       | B            |

| TNNLS        | B            |

| TITS         | B            |

| AISTATS      | C but top    |

| ICPR         | C            |

| Transportation Research Part C | SCI 1 Top |

Note that: AISTATS is CCF C but is top in computational mathematics (such as for probabilistic problems).

## ICML

>  Proceeding Page https://proceedings.mlr.press/

>  Homepage https://icml.cc

| Conference | Source                                                     | Deadline | Notification |

| ---------- | ---------------------------------------------------------- | ---------- | ---------- |

|ICML 2022|https://icml.cc/Conferences/2022/Schedule| Jan 27, 2022 |  |

|ICML 2021| [https://icml.cc/Conferences/2021/Schedule](https://icml.cc/Conferences/2021/Schedule)|  |  |

| ICML 2020 | [https://icml.cc/Conferences/2020/Schedule](https://icml.cc/Conferences/2020/Schedule) |  |  |

| ICML 2019  | [https://icml.cc/Conferences/2019/Schedule](https://icml.cc/Conferences/2019/Schedule)  |  |  |

## NeurIPS

[All Links](https://papers.NeurIPS.cc/)

## ICLR

Finding it on openreview:

> Homepage https://openreview.net/group?id=ICLR.cc

| Conference | Source                                                     | Deadline | Notification |

| ---------- | ---------------------------------------------------------- | ---------- | ---------- |

|ICLR 2022|https://openreview.net/group?id=ICLR.cc/2022/Conference|Oct 06 '21|Jan 24 '22|

| ICLR 2021  | [https://openreview.net/group?id=ICLR.cc/2021/Conference](https://openreview.net/group?id=ICLR.cc/2021/Conference) |  |  |

| ICLR 2020     | [https://openreview.net/group?id=ICLR.cc/2020/Conference](https://openreview.net/group?id=ICLR.cc/2020/Conference)     |  |  |

## KDD

> Format : https://www.kdd.org/kdd20xx/accepted-papers

| Conference | Source                                              | Deadline | Notification |

| ---------- | --------------------------------------------------- | ---------- | ---------- |

|KDD-22|| Feb 10th, 2022 | May 19th, 2022 |

|KDD-21| [Link](https://kdd.org/kdd2021/accepted-papers)|  |  |

| KDD-20     | [Link](https://www.kdd.org/kdd2020/accepted-papers) |  |  |

| KDD-19     | [Link](https://www.kdd.org/kdd2019/accepted-papers) |  |  |

| KDD-18     | [Link](https://www.kdd.org/kdd2018/accepted-papers) |  |  |

| KDD-17     | [Link](https://www.kdd.org/kdd2017/accepted-papers) |  |  |

## AAAI

| Conference | Source                                                       | Deadline          | Notification      |

| ---------- | ------------------------------------------------------------ | ----------------- | ----------------- |

|AAAI-22|[Link](https://aaai.org/Conferences/AAAI-22/wp-content/uploads/2021/12/AAAI-22_Accepted_Paper_List_Main_Technical_Track.pdf)|September 8, 2021|November 29, 2021|

| AAAI-21    | [Link](https://aaai.org/Conferences/AAAI-21/wp-content/uploads/2020/12/AAAI-21_Accepted-Paper-List.Main_.Technical.Track_.pdf) |                   |                   |

| AAAI-20    | [Link](https://aaai.org/Conferences/AAAI-20/wp-content/uploads/2020/01/AAAI-20-Accepted-Paper-List.pdf) |                   |                   |

| AAAI-19    | [Link](https://aaai.org/Conferences/AAAI-19/wp-content/uploads/2018/11/AAAI-19_Accepted_Papers.pdf) |                   |                   |

| AAAI-18    | [Link](https://aaai.org/Conferences/AAAI-18/wp-content/uploads/2017/12/AAAI-18-Accepted-Paper-List.Web_.pdf) |                   |                   |

| AAAI-17    | [Link](https://www.aaai.org/Conferences/AAAI/2017/aaai17accepted-papers.pdf) |                   |                   |

| AAAI-16    | [Link](https://www.aaai.org/Conferences/AAAI/2016/aaai16accepted-papers.pdf) |                   |                   |

| AAAI-15    | [Link](https://www.aaai.org/Conferences/AAAI/2015/iaai15accepted-papers.pdf) |                   |                   |

| AAAI-14    | [Link](https://www.aaai.org/Conferences/AAAI/2014/aaai14accepts.php) |                   |                   |

| AAAI-13    | [Link](https://www.aaai.org/Conferences/AAAI/2013/aaai13accepts.php) |                   |                   |

## [IJCAI](https://www.ijcai.org/past_proceedings)

| Conference | Source                                                      | Deadline | Notification |

| ---------- | ----------------------------------------------------------- | ---------- | ---------- |

|IJCAI-22| [Link](https://www.ijcai.org/proceedings/2022/)   |  |

|IJCAI-21|[Link](https://ijcai-21.org/program-main-track/)|  |  |

| IJCAI-20   | [Link](http://static.ijcai.org/2020-accepted_papers.html)   |  |  |

| IJCAI-19   | [Link](https://www.ijcai19.org/accepted-papers.html)        |  |  |

| IJCAI-18   | [Link](https://www.ijcai-18.org/accepted-papers/index.html) |  |  |

| IJCAI-17   | [Link](https://ijcai-17.org/accepted-papers.html)           |  |  |

| IJCAI-16   | [Link](https://www.ijcai.org/proceedings/2016)              |  |  |

| IJCAI-15   | [Link](https://www.ijcai.org/Proceedings/2015)              |  |  |

| IJCAI-14   | None                                                        |  |  |

## ICDE

IEEE International Conference on Data Engineering

[All Links](https://ieeexplore.ieee.org/xpl/conhome/1000178/all-proceedings)

## WWW

TheWebConf

| Conference | Source                                                     | Deadline | Notification |

| ---------- | ---------------------------------------------------------- | ---------- | ---------- |

|WWW-22| [Link](https://www2022.thewebconf.org/accepted-papers/)| 2021-10-21 ... | 2022-01-13 ... |

|WWW-21| [Link](https://www2021.thewebconf.org/program/papers/)|  |  |

| WWW-20     | [Link](https://dl.acm.org/doi/proceedings/10.1145/3366423) |  |  |

| WWW-19     | [Link](https://www2019.thewebconf.org/accepted-papers)     |  |  |

| WWW-18     | [Link](https://dl.acm.org/doi/proceedings/10.5555/3178876) |  |  |

| WWW-17     | [Link](https://dl.acm.org/doi/proceedings/10.1145/3308558) |  |  |

## CIKM

The Conference on Information and Knowledge Management

[All Links](https://dl.acm.org/conference/cikm)

## ICDM

IEEE International Conference on Data Mining

[All Links]([https://dl.acm.org/conference/cikm](https://ieeexplore.ieee.org/xpl/conhome/1000179/all-proceedings))

## WSDM

ACM Web Search and Data Mining

[All Links](https://dl.acm.org/conference/wsdm)
ecosyste.ms

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