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awesome-anomaly-detection

A complete list of papers on anomaly detection.
https://github.com/zhuyiche/awesome-anomaly-detection

Last synced: 2 days ago
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Classical Method
- - Isolation Forest - ICDM 2008.
  - LOF: Identifying Density-Based Local Outliers - SIGMOD 2000.
  - Extended Isolation Forest
  - Robust Random Cut Forest Based Anomaly Detection On Streams
  - Support Vector Method for Novelty Detection - NIPS 2000
- One-Class Classification
  - One-Class SVMs for Document Classification - JMLR 2001.
  - Support Vector Data Description
  - Can I Trust My One-Class Classification?
  - Efficient Anomaly Detection via Matrix Sketching - NIPS 2018
  - Efficient Anomaly Detection via Matrix Sketching - NIPS 2018
- PCA-based
  - robust deep and inductive anomaly detection - ECML PKDD 2017
- Clustering
  - A Practical Algorithm for Distributed Clustering and Outlier Detection - NIPS 2018
  - A Practical Algorithm for Distributed Clustering and Outlier Detection - NIPS 2018
- Correlation
  - Detecting Multiple Periods and Periodic Patterns in Event Time Sequences - CIKM 2017.
- Ranking
  - ranking causal anomalies via temporal and dynamical analysis on vanishing correlations - KDD 2016.
- Streaming
  - MIDAS: Microcluster-Based Detector of Anomalies in Edge Streams - AAAI 2020.
Deep Learning Method
- Generative Methods
  - Variational Autoencoder based Anomaly Detection using Reconstruction Probability
  - Learning sparse representation with variational auto-encoder for anomaly detection
  - Anomaly Detection with Robust Deep Autoencoders - KDD 2017.
  - DEEP AUTOENCODING GAUSSIAN MIXTURE MODEL FOR UNSUPERVISED ANOMALY DETECTION - ICLR 2018.
  - Multidimensional Time Series Anomaly Detection: A GRU-based Gaussian Mixture Variational Autoencoder Approach - ACML 2018
  - A Multimodel Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder - IEEE Robotics and Automation Letters 2018.
  - Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discovery - IPMI 2017.
  - Anomaly detection with generative adversarial networks - Reject by ICLR 2018, but was used as baseline method in recent published NIPS paper.
  - Anomaly Detection with Robust Deep Autoencoders - KDD 2017.
  - A Multimodel Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder - IEEE Robotics and Automation Letters 2018.
- Hypersphereical Learning
  - Deep into Hypersphere: Robust and Unsupervised Anomaly Discovery in Dynamic Networks - IJCAI 2018.
- One-Class Classification
  - High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning - Pattern Recognition 2018.
  - Optimal single-class classification strategies - NIPS 2007.
  - Deep One-Class Classification - ICML 2018.
  - Deep Semi-Supervised Anomaly Detection - ICLR 2020.
  - Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification - IJCNN 2021
  - Explainable Deep One-Class Classification
  - Learning and Evaluating Representation for Deep One-Class Classification
  - Simple and Effective Prevention of Mode Collapse in Deep One-Class Classification - IJCNN 2021
- Energy-based
  - Deep structured energy based models for anomaly detection - ICML 2016
  - Deep structured energy based models for anomaly detection - ICML 2016
- Time series
  - A Generalized Student-t Based Approach to Mixed-Type Anomaly Detection - AAAI 2013
  - Stochastic Online Anomaly Analysis for Streaming Time Series - IJCAI 2017
  - Long short term memory networks for anmomaly detection in time series
  - LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection - ICML 2016 Workshop.
  - LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection - ICML 2016 Workshop.
- Interpretation
  - Contextual Outlier Interpretation - IJCAI 2018
- Evaulation Metrics
  - Precision and Recall for Time Series - NIPS 2018
- Geometric transformation
  - Deep Anomaly Detection Using Geometric Transformations - NIPS 2018
  - Deep Anomaly Detection Using Geometric Transformations - NIPS 2018
- FeedBack
  - Feedback-Guided Anomaly Discovery via Online Optimization - KDD 2018.
Anomaly Detection Applications
- KPI
- Log
  - Loganomaly: Unsupervised detection of sequential and quantitative anomalies in unstructured logs - IJCAI 2019
  - Robust log-based anomaly detection on unstable log data - FSE 2019
  - DeepLog: Anomaly Detection and Diagnosis from System Logs through Deep Learning - CCS 2017
  - Mining Invariants from Logs for System Problem Detection - USENIX 2010
  - Prefix: Switch failure prediction in datacenter networks - SIGMETRICS 2018
Survey
- Log

Categories

Survey 45 Deep Learning Method 31 Classical Method 16 Anomaly Detection Applications 8

Sub Categories

Log 50 One-Class Classification 13 Generative Methods 10 Time series 5 KPI 3 Geometric transformation 2 Energy-based 2 Clustering 2 FeedBack 1 Streaming 1 Correlation 1 Ranking 1 Hypersphereical Learning 1 Interpretation 1 Evaulation Metrics 1 PCA-based 1