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https://github.com/AXYZdong/awesome-snn-conference-paper

🔥 This repo collects top international conference papers, codes about Spiking Neural Networks. 本仓库收集了脉冲神经网络领域的顶会顶刊论文和代码，正在持续更新中。
https://github.com/AXYZdong/awesome-snn-conference-paper

List: awesome-snn-conference-paper

awesome awesome-list brain-inspired-computing conference-paper neuromorphic-computing paper-list snn spiking-neural-network spiking-neural-networks

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🔥 This repo collects top international conference papers, codes about Spiking Neural Networks. 本仓库收集了脉冲神经网络领域的顶会顶刊论文和代码，正在持续更新中。

Awesome Lists containing this project

README 

        
# Awesome SNN Conference Paper [![Awesome](https://awesome.re/badge-flat.svg)](https://awesome.re)



🔥 This repo collects top international conference papers, codes about **Spiking Neural Networks** for anyone who wants to do research on it. We are continuously improving the project. 



The part of 2018-2021 is referenced in  [Awesome-SNN-Paper-Collection](https://github.com/Ruichen0424/Awesome-SNN-Paper-Collection).



The part of 2022 is referenced in [2022年顶会、顶刊SNN相关论文](https://blog.csdn.net/qq_43622216/article/details/124163883).



Thank the repo or blogs for their contributions to the collection of papers from top conferences or top journals in the SNN field.



🤗 Welcome anyone who is interested to contribute to the repo together ! If you find another papers that are not in this repo, you can **pull requests**.



❤Thanks so much @[Ruichen0424](https://github.com/Ruichen0424) for the collaboration!



---



  Table of Contents (Conferences by Year) 

  
    

          

        
  1. 

    2025

          

        
    2. 

          

        
  2. 

    2024

          

        
    3. 

          

        
  3. 

    2023

          

        
    4. 

          

        
  4. 

    2022

          

        
    5. 

           

        
  5. 

          2021

          

        
    6. 

        

        
  6. 

          2020

          

        
    7. 

        

        
  7. 

          2019

          

        
    8. 

        

        
  8. 

          2018

          

        
    9. 

      



**Abbreviation - Full Name List**



| Abbreviation |                                Full Name                                 |

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

|     CVPR     |        IEEE Conference on Computer Vision and Pattern Recognition        |

|     ICCV     |             IEEE International Conference on Computer Vision             |

|   NeurIPS    |           Conference on Neural Information Processing Systems            |

|     AAAI     |        Association for the Advancement of Artificial Intelligence        |

|     ICLR     |           International Conference on Learning Representations           |

|     ICML     |               International Conference on Machine Learning               |

|     ECCV     |                  European Conference on Computer Vision                  |

|    IJCAI     |        International Joint Conference on Artificial Intelligence         |

|    ICASSP    | IEEE International Conference on Acoustics, Speech and Signal Processing |

|    IJCNN     |            International Joint Conference on Neural Networks             |

|     PAMI     |      IEEE Transactions on Pattern Analysis and Machine Intelligence      |

|    TNNLS     |        IEEE Transactions on Neural Networks and Learning Systems         |



---



# 2025



## CVPR-2025



- Spiking Transformer: Introducing Accurate Addition-Only Spiking Self-Attention for Transformer [[paper](https://cvpr.thecvf.com/virtual/2025/poster/33151)]

 

- Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering [[paper](https://cvpr.thecvf.com/virtual/2025/poster/33079)]

 

- STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks [[paper](https://cvpr.thecvf.com/virtual/2025/poster/34574)] [[arxiv](https://arxiv.org/abs/2503.02689v2)] [[paper with code](https://paperswithcode.com/paper/staa-snn-spatial-temporal-attention)]

 

- USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting [[paper](https://cvpr.thecvf.com/virtual/2025/poster/34321)] [[arxiv](https://arxiv.org/abs/2411.10504v1)] [[paper with code](https://paperswithcode.com/paper/usp-gaussian-unifying-spike-based-image)] [[code](https://github.com/chenkang455/usp-gaussian)]

 

- Spiking Transformer with Spatial-Temporal Attention [[paper](https://cvpr.thecvf.com/virtual/2025/poster/34119)] [[arxiv](https://arxiv.org/abs/2409.19764v2)] [[paper with code](https://paperswithcode.com/paper/spiking-transformer-with-spatial-temporal)]

 

- Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacement [[paper](https://cvpr.thecvf.com/virtual/2025/poster/34359)]



## ICLR-2025



- SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking [[paper](https://iclr.cc/virtual/2025/poster/29210)] [[arxiv](https://arxiv.org/abs/2407.04752v1)] [[paper with code](https://paperswithcode.com/paper/spikellm-scaling-up-spiking-neural-network-to)] [[code](https://github.com/xingrun-xing/spikelm)]



- QP-SNN: Quantized and Pruned Spiking Neural Networks [[paper](https://iclr.cc/virtual/2025/poster/29921)]



- P-SPIKESSM: HARNESSING PROBABILISTIC SPIKING STATE SPACE MODELS FOR LONG-RANGE DEPENDENCY TASKS [[paper](https://iclr.cc/virtual/2025/poster/29587)] [[arxiv](https://arxiv.org/abs/2406.02923v2)] [[paper with code](https://paperswithcode.com/paper/rethinking-spiking-neural-networks-as-state)]



- Spiking Vision Transformer with Saccadic Attention [[paper](https://iclr.cc/virtual/2025/poster/28227)]



- DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks [[paper](https://iclr.cc/virtual/2025/poster/28961)]



- Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness [[paper](https://iclr.cc/virtual/2025/poster/30705)]



- Quantized Spike-driven Transformer [[paper](https://iclr.cc/virtual/2025/poster/30954)] [[arxiv](https://arxiv.org/abs/2501.13492v2)] [[paper with code](https://paperswithcode.com/paper/quantized-spike-driven-transformer)] [[code](https://github.com/bollossom/qsd-transformer)]



- SPAM: Spike-Aware Adam with Momentum Reset for Stable LLM Training [[paper](https://iclr.cc/virtual/2025/poster/30015)] [[arxiv](https://arxiv.org/abs/2501.06842v1)] [[paper with code](https://paperswithcode.com/paper/spam-spike-aware-adam-with-momentum-reset-for)] [[code](https://github.com/tianjinyellow/spam-optimizer)]



- TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting [[paper](https://iclr.cc/virtual/2025/poster/28210)]



- Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency [[paper](https://iclr.cc/virtual/2025/poster/28809)]



- Rethinking Spiking Neural Networks from an Ensemble Learning Perspective [[paper](https://iclr.cc/virtual/2025/poster/29191)] [[arxiv](https://arxiv.org/abs/2502.14218v1)] [[paper with code](https://paperswithcode.com/paper/rethinking-spiking-neural-networks-from-an)]



# 2024



## NeurIPS-2024



- Latent Diffusion for Neural Spiking Data [[paper](https://nips.cc/virtual/2024/poster/94632)] [[arxiv](https://arxiv.org/abs/2407.08751v1)] [[paper with code](https://paperswithcode.com/paper/latent-diffusion-for-neural-spiking-data)]

 

- Spiking Transformer with Experts Mixture [[paper](https://nips.cc/virtual/2024/poster/94824)]

 

- Autonomous Driving with Spiking Neural Networks [[paper](https://nips.cc/virtual/2024/poster/96329)] [[arxiv](https://arxiv.org/abs/2405.19687v2)] [[paper with code](https://paperswithcode.com/paper/autonomous-driving-with-spiking-neural)] [[code](https://github.com/ridgerchu/sad)]

 

- Rethinking the Dynamics of Spiking Neural Networks [[paper](https://nips.cc/virtual/2024/poster/96543)]

 

- Spiking Graph Neural Network on Riemannian Manifolds [[paper](https://nips.cc/virtual/2024/poster/94910)] [[arxiv](https://arxiv.org/abs/2410.17941v1)] [[paper with code](https://paperswithcode.com/paper/spiking-graph-neural-network-on-riemannian)] [[code](https://github.com/ZhenhHuang/MSG)]

 

- Spiking Neural Network as Adaptive Event Stream Slicer [[paper](https://nips.cc/virtual/2024/poster/96133)] [[arxiv](https://arxiv.org/abs/2410.02249v1)] [[paper with code](https://paperswithcode.com/paper/spiking-neural-network-as-adaptive-event)]

 

- Spike-based Neuromorphic Model for Sound Source Localization [[paper](https://nips.cc/virtual/2024/poster/96112)]

 

- QKFormer: Hierarchical Spiking Transformer using Q-K Attention [[paper](https://nips.cc/virtual/2024/poster/96252)] [[arxiv](https://arxiv.org/abs/2403.16552v2)] [[paper with code](https://paperswithcode.com/paper/qkformer-hierarchical-spiking-transformer)] [[code](https://github.com/zhouchenlin2096/qkformer)]

 

- Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals [[paper](https://nips.cc/virtual/2024/poster/93768)] [[arxiv](https://arxiv.org/abs/2405.13587v1)] [[paper with code](https://paperswithcode.com/paper/exact-gradients-for-stochastic-spiking-neural)]

 

- Neuronal Competition Groups with Supervised STDP for Spike-Based Classification [[paper](https://nips.cc/virtual/2024/poster/95890)] [[arxiv](https://arxiv.org/abs/2410.17066v1)] [[paper with code](https://paperswithcode.com/paper/neuronal-competition-groups-with-supervised)]

 

- Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover [[paper](https://nips.cc/virtual/2024/poster/96690)]

 

- Continuous Spatiotemporal Events Decoupling through Spike-based Bayesian Computation [[paper](https://nips.cc/virtual/2024/poster/92957)]

 

- SpikeReveal: Unlocking Temporal Sequences from Real Blurry Inputs with Spike Streams [[paper](https://nips.cc/virtual/2024/poster/96319)] [[arxiv](https://arxiv.org/abs/2403.09486v5)] [[paper with code](https://paperswithcode.com/paper/spikereveal-unlocking-temporal-sequences-from)] [[code](https://github.com/chenkang455/s-sdm)]

 

- Spiking Token Mixer: A event-driven friendly Former structure for spiking neural networks [[paper](https://nips.cc/virtual/2024/poster/93999)]

 

- Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras [[paper](https://nips.cc/virtual/2024/poster/95131)]

 

- Advancing Spiking Neural Networks for Sequential Modeling through Central Pattern Generators [[paper](https://nips.cc/virtual/2024/poster/93894)]

 

- Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks [[paper](https://nips.cc/virtual/2024/poster/93065)] [[arxiv](https://arxiv.org/abs/2401.04486v2)] [[paper with code](https://paperswithcode.com/paper/take-a-shortcut-back-mitigating-the-gradient)]

 

- Towards a "Universal Translator" for Neural Dynamics at Single-Cell, Single-Spike Resolution [[paper](https://nips.cc/virtual/2024/poster/93693)] [[arxiv](https://arxiv.org/abs/2407.14668v2)] [[paper with code](https://paperswithcode.com/paper/towards-a-universal-translator-for-neural)]

 

- FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor [[paper](https://nips.cc/virtual/2024/poster/95008)]

 

- EnOF: Training Accurate Spiking Neural Networks via Enhancing the Output Feature Representation [[paper](https://nips.cc/virtual/2024/poster/95074)]

 

- Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation [[paper](https://nips.cc/virtual/2024/poster/93126)] [[arxiv](https://arxiv.org/abs/2410.11488v2)] [[paper with code](https://paperswithcode.com/paper/advancing-training-efficiency-of-deep-spiking)] [[code](https://github.com/tab-ct/rate-based-backpropagation)]

 

- Statistical Estimation in the Spiked Tensor Model via the Quantum Approximate Optimization Algorithm [[paper](https://nips.cc/virtual/2024/poster/94828)]

 

- SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network [[paper](https://nips.cc/virtual/2024/poster/95897)] [[arxiv](https://arxiv.org/abs/2405.14398v2)] [[paper with code](https://paperswithcode.com/paper/spgesture-source-free-domain-adaptive-semg)] [[code](https://github.com/guoweiyu/spgesture)]

 

- Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli [[paper](https://nips.cc/virtual/2024/poster/94454)]

 

- SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation [[paper](https://nips.cc/virtual/2024/poster/94181)]



## IJCAI-2024



- Learning a Spiking Neural Network for Efficient Image Deraining  [[arxiv](https://arxiv.org/abs/2405.06277v1)] [[paper with code](https://paperswithcode.com/paper/learning-a-spiking-neural-network-for)] [[code](https://github.com/mingtian99/esdnet)]

 

- LitE-SNN: Designing Lightweight and Efficient Spiking Neural Network through Spatial-Temporal Compressive Network Search and Joint Optimization  [[arxiv](https://arxiv.org/abs/2401.14652v2)] [[paper with code](https://paperswithcode.com/paper/lite-snn-designing-lightweight-and-efficient)]

 

- TIM: An Efficient Temporal Interaction Module for Spiking Transformer [[arxiv](https://arxiv.org/abs/2401.11687v3)] [[paper with code](https://paperswithcode.com/paper/tim-an-efficient-temporal-interaction-module)] [[code](https://github.com/BrainCog-X/Brain-Cog/tree/main/examples/TIM)]

 

- One-step Spiking Transformer with a Linear Complexity

 

- EC-SNN: Splitting Deep Spiking Neural Networks for Edge Devices

 

- Apprenticeship-Inspired Elegance: Synergistic Knowledge Distillation Empowers Spiking Neural Networks for Efficient Single-Eye Emotion Recognition  [[arxiv](https://arxiv.org/abs/2407.09521v1)] [[paper with code](https://paperswithcode.com/paper/apprenticeship-inspired-elegance-synergistic)]



## ICML-2024



- CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [[paper](https://openreview.net/attachment?id=yY6N89IlHa&name=pdf)] [[arxiv](https://arxiv.org/abs/2402.04663v4)] [[paper with code](https://paperswithcode.com/paper/clif-complementary-leaky-integrate-and-fire)] [[code](https://github.com/huuyulong/complementary-lif)]

 

- High-Performance Temporal Reversible Spiking Neural Networks with O(L) Training Memory and O(1) Inference Cost [[paper](https://openreview.net/attachment?id=s4h6nyjM9H&name=pdf)]



- SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN [[paper](https://openreview.net/attachment?id=NeotatlYOL&name=pdf)] [[arxiv](https://arxiv.org/abs/2406.03470v1)] [[paper with code](https://paperswithcode.com/paper/spikezip-tf-conversion-is-all-you-need-for#code)] [[code](https://github.com/Intelligent-Computing-Research-Group/SpikeZIP-TF)]

 

- NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks [[paper](https://openreview.net/attachment?id=elF0QoBSFV&name=pdf)]

 

- Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration [[paper](https://openreview.net/attachment?id=yL6hljtjW4&name=pdf)]

 

- Efficient and Effective Time-Series Forecasting with Spiking Neural Networks [[paper](https://openreview.net/attachment?id=SkI6u81AkI&name=pdf)] [[arxiv](https://arxiv.org/abs/2402.01533v2)] [[paper with code](https://paperswithcode.com/paper/efficient-and-effective-time-series#code)] [[code](https://github.com/microsoft/seqsnn)]

 

- Balanced Resonate-and-Fire Neurons [[paper](https://openreview.net/attachment?id=dkdilv4XD4&name=pdf)]

 

- SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms [[paper](https://openreview.net/attachment?id=4PB1RMsUy4&name=pdf)] [[arxiv](https://arxiv.org/abs/2406.03287v1)] [[paper with code](https://paperswithcode.com/paper/spikelm-towards-general-spike-driven-language#code)] [[code](https://github.com/xingrun-xing/spikelm)]

 

- Robust Stable Spiking Neural Networks [[paper](https://openreview.net/attachment?id=lIYtJtpJR0&name=pdf)] [[arxiv](https://arxiv.org/abs/2405.20694v1)] [[paper with code](https://paperswithcode.com/paper/robust-stable-spiking-neural-networks#code)] [[code](https://github.com/DingJianhao/stable-snn)]

 

- Conditionally-Conjugate Gaussian Process Factor Analysis for Spike Count Data via Data Augmentation [[paper](https://openreview.net/attachment?id=zgiT3uxvCF&name=pdf)]

 

- Towards efficient deep spiking neural networks construction with spiking activity based pruning [[paper](https://openreview.net/attachment?id=eMQyb1tvvc&name=pdf)]

 

- Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning [[paper](https://openreview.net/attachment?id=3FeYlKIPr3&name=pdf)] [[arxiv](https://arxiv.org/abs/2405.16851v1)] [[paper with code](https://paperswithcode.com/paper/temporal-spiking-neural-networks-with#code)] [[code](https://github.com/pkuxmq/grsnn)]



- Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network [[paper](https://openreview.net/attachment?id=kfpe7Dg23G&name=pdf)]  [[arxiv](https://arxiv.org/pdf/2407.01645v1.pdf)] [[paper with code](https://paperswithcode.com/paper/sign-gradient-descent-based-neuronal-dynamics#code)] [[code](https://github.com/snuhcs/snn_signgd)]



- Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks [[paper](https://openreview.net/attachment?id=kAIkYOE5pV&name=pdf)] [[arxiv](https://arxiv.org/abs/2406.00405v2)] [[paper with code](https://paperswithcode.com/paper/autaptic-synaptic-circuit-enhances-spatio#code)] [[code](https://github.com/wangtianyi1874/stclif)]

 

- Enhancing Adversarial Robustness in SNNs with Sparse Gradients [[paper](https://openreview.net/attachment?id=QvABoVGdRp&name=pdf)]



## AAAI-2024



- Enhancing the Robustness of Spiking Neural Networks with Stochastic Gating Mechanisms [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27804)]



- An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27806)] [[arxiv](https://arxiv.org/abs/2303.13077)] [[paper with code](https://paperswithcode.com/paper/improving-the-performance-of-spiking-neural)] [[code](https://github.com/brain-cog-lab/transfer-for-dvs)]



- Gated Attention Coding for Training High-Performance and Efficient Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27816)] [[arxiv](https://arxiv.org/abs/2308.06582)] [[paper with code](https://paperswithcode.com/paper/gated-attention-coding-for-training-high)] [[code](https://github.com/bollossom/GAC)]



- Efficient Spiking Neural Networks with Sparse Selective Activation for Continual Learning [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27817)]



- DeblurSR: Event-Based Motion Deblurring under the Spiking Representation [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28293)] [[arxiv](https://arxiv.org/abs/2303.08977)] [[paper with code](https://paperswithcode.com/paper/deblursr-event-based-motion-deblurring-under)] [[code](https://github.com/chensong1995/deblursr)]



- Point-to-Spike Residual Learning for Energy-Efficient 3D Point Cloud Classification [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28425)]



- Finding Visual Saliency in Continuous Spike Stream [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28610)] [[arxiv](https://arxiv.org/abs/2403.06233)] [[paper with code](https://paperswithcode.com/paper/finding-visual-saliency-in-continuous-spike)] [[code](https://github.com/bit-vision/svs)]



- Enhancing Training of Spiking Neural Network with Stochastic Latency [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28964)]



- SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28975)] [[arxiv](https://arxiv.org/abs/2308.10873)] [[paper with code](https://paperswithcode.com/paper/spikingbert-distilling-bert-to-train-spiking)] [[code](https://github.com/neurocomplab-psu/spikingbert)]



- Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29066)] [[arxiv](https://arxiv.org/abs/2401.01912)]



- Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29114)] [[arxiv](https://arxiv.org/abs/2312.06372)] [[paper with code](https://paperswithcode.com/paper/ternary-spike-learning-ternary-spikes-for)] [[code](https://github.com/yfguo91/ternary-spike)]



- Spiking NeRF: Representing the Real-World Geometry by a Discontinuous Representation [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29285)] [[arxiv](https://arxiv.org/abs/2311.09077)] [[paper with code](https://paperswithcode.com/paper/spiking-nerf-representing-the-real-world)] [[code](https://github.com/liaozhanfeng/spiking-nerf)]



- Dynamic Spiking Graph Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29587)] [[arxiv](https://arxiv.org/abs/2401.05373)] [[paper with code](https://paperswithcode.com/paper/dynamic-spiking-graph-neural-networks)]



- Memory-Efficient Reversible Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29616)] [[arxiv](https://arxiv.org/abs/2312.07922)] [[paper with code](https://paperswithcode.com/paper/memory-efficient-reversible-spiking-neural)] [[code](https://github.com/mi804/revsnn)]



- TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29625)] [[arxiv](https://arxiv.org/abs/2308.13250)] [[paper with code](https://paperswithcode.com/paper/tc-lif-a-two-compartment-spiking-neuron-model)] [[code](https://github.com/zhangshimin1/tc-lif)]



- Enhancing Representation of Spiking Neural Networks via Similarity-Sensitive Contrastive Learning [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29635)]



- Dynamic Reactive Spiking Graph Neural Network [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/29640)]



- Transient Glimpses: Unveiling Occluded Backgrounds through the Spike Camera [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27820)]



- Joint Demosaicing and Denoising for Spike Camera [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/27924)]



- Recognizing Ultra-High-Speed Moving Objects with Bio-Inspired Spike Camera [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28579)]



- Optical Flow for Spike Camera with Hierarchical Spatial-Temporal Spike Fusion [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/28581)]



- Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training [[paper](https://arxiv.org/abs/2312.09391)]



## ICLR-2024



- Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? [[paper](https://iclr.cc/virtual/2024/poster/17942)] [[openreview](https://openreview.net/forum?id=lGUyAuuTYZ)]



- LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units [[paper](https://iclr.cc/virtual/2024/poster/17828)] [[arxiv](https://arxiv.org/abs/2402.04882)] [[paper with code](https://paperswithcode.com/paper/lmuformer-low-complexity-yet-powerful-spiking)] [[code](https://github.com/zeyuliu1037/lmuformer)] [[openreview](https://openreview.net/forum?id=oEF7qExD9F)]



- Threaten Spiking Neural Networks through Combining Rate and Temporal Information [[paper](https://iclr.cc/virtual/2024/poster/17437)] [[openreview](https://openreview.net/forum?id=xv8iGxENyI)]



- TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks [[paper](https://iclr.cc/virtual/2024/poster/17995)] [[openreview](https://openreview.net/forum?id=k1wlmtPGLq)]



- Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks [[paper](https://iclr.cc/virtual/2024/poster/19423)] [[openreview](https://openreview.net/forum?id=5bNYf0CqxY)]



- Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN [[paper](https://iclr.cc/virtual/2024/poster/19606)] [[arxiv](https://arxiv.org/abs/2403.03409)] [[paper with code](https://paperswithcode.com/paper/sparse-spiking-neural-network-exploiting)] [[openreview](https://openreview.net/forum?id=0jsfesDZDq)]



- Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures [[paper](https://iclr.cc/virtual/2024/poster/18391)] [[arxiv](https://arxiv.org/abs/2309.02213)] [[openreview](https://openreview.net/forum?id=ZYm1Ql6udy)]



- Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers [[paper](https://iclr.cc/virtual/2024/poster/18442)] [[openreview](https://openreview.net/forum?id=XrunSYwoLr)]



- Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism [[paper](https://iclr.cc/virtual/2024/poster/17478)] [[openreview](https://openreview.net/forum?id=wpnlc2ONu0)]



- Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings [[paper](https://iclr.cc/virtual/2024/poster/19447)] [[arxiv](https://arxiv.org/abs/2306.17670)] [[paper with code](https://paperswithcode.com/paper/learning-delays-in-spiking-neural-networks)] [[code](https://github.com/thvnvtos/snn-delays)] [[openreview](https://openreview.net/forum?id=4r2ybzJnmN)]



- Online Stabilization of Spiking Neural Networks [[paper](https://iclr.cc/virtual/2024/poster/19180)] [[openreview](https://openreview.net/forum?id=CIj1CVbkpr)]



- Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips [[paper](https://iclr.cc/virtual/2024/poster/19587)] [[openreview](https://openreview.net/forum?id=1SIBN5Xyw7)]



- A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model [[paper](https://iclr.cc/virtual/2024/poster/18160)] [[openreview](https://openreview.net/forum?id=g52tgL8jy6)]



- Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework [[paper](https://iclr.cc/virtual/2024/poster/18207)] [[openreview](https://openreview.net/forum?id=eoSeaK4QJo)]



- Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks [[paper](https://iclr.cc/virtual/2024/poster/18815)] [[arxiv](https://arxiv.org/abs/2402.11984)] [[paper with code](https://paperswithcode.com/paper/hebbian-learning-based-orthogonal-projection)] [[code](https://github.com/pkuxmq/hlop-snn)] [[openreview](https://openreview.net/forum?id=MeB86edZ1P)]



- A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks [[paper](https://iclr.cc/virtual/2024/poster/18850)] [[arxiv](https://arxiv.org/abs/2305.19306)] [[paper with code](https://paperswithcode.com/paper/a-graph-is-worth-1-bit-spikes-when-graph)] [[code](https://github.com/edisonleeeee/spikegcl)] [[openreview](https://openreview.net/forum?id=LnLySuf1vp)]



- SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition [[paper](https://iclr.cc/virtual/2024/poster/19352)] [[arxiv](https://arxiv.org/abs/2310.07189)] [[paper with code](https://paperswithcode.com/paper/spikepoint-an-efficient-point-based-spiking)] [[openreview](https://openreview.net/forum?id=7etoNfU9uF)]



- EventRPG: Event Data Augmentation with Relevance Propagation Guidance [[paper](https://arxiv.org/abs/2403.09274)] [[code](https://github.com/myuansun/EventRPG)]



## CVPR-2024



- SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks [[paper](https://arxiv.org/pdf/2403.14302.pdf)] [[code](https://github.com/xyshi2000/SpikingResformer)]



- Are Conventional SNNs Really Efficient? A Perspective from Network Quantization [[paper](https://arxiv.org/pdf/2311.10802.pdf)]



- SFOD: Spiking Fusion Object Detector [[paper](https://arxiv.org/abs/2403.15192)] [[code](https://github.com/yimeng-fan/SFOD)]



## ECCV-2024



- Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision [[paper](https://eccv2024.ecva.net//virtual/2024/poster/1172)]

 

- BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation [[paper](https://eccv2024.ecva.net//virtual/2024/poster/2655)] [[arxiv](https://arxiv.org/abs/2407.09083v2)] [[paper with code](https://paperswithcode.com/paper/bkdsnn-enhancing-the-performance-of-learning)] [[code](https://github.com/intelligent-computing-research-group/bkdsnn)]

 

- EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networks [[paper](https://eccv2024.ecva.net//virtual/2024/poster/711)] [[arxiv](https://arxiv.org/abs/2403.12574v2)] [[paper with code](https://paperswithcode.com/paper/eas-snn-end-to-end-adaptive-sampling-and)] [[code](https://github.com/windere/eas-snn)]

 

- Efficient Training of Spiking Neural Networks with Multi-Parallel Implicit Stream Architecture [[paper](https://eccv2024.ecva.net//virtual/2024/poster/1548)]

 

- Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data [[paper](https://eccv2024.ecva.net//virtual/2024/poster/1447)]

 

- Integer-Valued Training and Spike-driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection [[paper](https://eccv2024.ecva.net//virtual/2024/poster/150)] [[arxiv](https://arxiv.org/abs/2407.20708v3)] [[paper with code](https://paperswithcode.com/paper/integer-valued-training-and-spike-driven)] [[code](https://github.com/biclab/spikeyolo)]

 

- Learning to Robustly Reconstruct Dynamic Scenes from Low-light Spike Streams [[paper](https://eccv2024.ecva.net//virtual/2024/poster/1641)]

 

- Real-data-driven 2000 FPS Color Video from Mosaicked Chromatic Spikes [[paper](https://eccv2024.ecva.net//virtual/2024/poster/2019)]

 

- Spike-Temporal Latent Representation for Energy-Efficient Event-to-Video Reconstruction [[paper](https://eccv2024.ecva.net//virtual/2024/poster/1446)]

 

- Spiking Wavelet Transformer [[paper](https://eccv2024.ecva.net//virtual/2024/poster/2545)] [[arxiv](https://arxiv.org/abs/2403.11138v5)] [[paper with code](https://paperswithcode.com/paper/spiking-wavelet-transformer)] [[code](https://github.com/bic-l/spiking-wavelet-transformer)]



## ICASSP-2024



- sVAD: A Robust, Low-Power, and Light-Weight Voice Activity Detection with Spiking Neural Networks [[paper](https://arxiv.org/abs/2403.05772)]



- Optimal ANN-SNN Conversion with Group Neurons [[paper](https://arxiv.org/abs/2402.19061)] [[code](https://github.com/Lyu6PosHao/ANN2SNN_GN)]



## PAMI-2024



- A Hybrid Neural Coding Approach for Pattern Recognition With Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/10347028)] [[arxiv](https://arxiv.org/abs/2305.16594v2)] [[paper with code](https://paperswithcode.com/paper/a-hybrid-neural-coding-approach-for-pattern)] [[code](https://github.com/xychen-comp/hybrid-coding-snn)]



- Developmental Plasticity-inspired Adaptive Pruning for Deep Spiking and Artificial Neural Networks [[paper](https://ieeexplore.ieee.org/document/10691937)] [[arxiv](https://arxiv.org/abs/2211.12714v3)] [[paper with code](https://paperswithcode.com/paper/developmental-plasticity-inspired-adaptive)]



## TNNLS-2024



- Advancing Spiking Neural Networks Toward Deep Residual Learning [[paper](https://ieeexplore.ieee.org/abstract/document/10428029)] [[arxiv](https://arxiv.org/abs/2112.08954v3)] [[paper with code](https://paperswithcode.com/paper/advancing-residual-learning-towards-powerful)] [[code](https://github.com/ariande1/ms-resnet)]



- Adaptive Synaptic Scaling in Spiking Networks for Continual Learning and Enhanced Robustness [[paper](https://ieeexplore.ieee.org/document/10479209)]



- Spiking Neural Network for Ultralow-Latency and High-Accurate Object Detection [[paper](https://ieeexplore.ieee.org/document/10472977)]

 

- TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/10496285)] [[arxiv](https://arxiv.org/abs/2206.10177v3)] [[paper with code](https://paperswithcode.com/paper/tcja-snn-temporal-channel-joint-attention-for)] [[code](https://github.com/ridgerchu/TCJA)]

 

- Fully Spiking Actor Network With Intralayer Connections for Reinforcement Learning [[paper](https://ieeexplore.ieee.org/document/10423179)]



- Minicolumn-Based Episodic Memory Model With Spiking Neurons, Dendrites and Delays [[paper](https://ieeexplore.ieee.org/document/9927446)]

 

- Efficient Deep Spiking Multilayer Perceptrons With Multiplication-Free Inference [[paper](https://ieeexplore.ieee.org/document/10535518)]

 

- CDNA-SNN: A New Spiking Neural Network for Pattern Classification Using Neuronal Assemblies [[paper](https://ieeexplore.ieee.org/document/10428047)]



- Accurate and Efficient Event-Based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network [[paper](https://ieeexplore.ieee.org/document/10645685)] [[arxiv](https://arxiv.org/abs/2304.11857v3)] [[paper with code](https://paperswithcode.com/paper/accurate-and-efficient-event-based-semantic)]



- Retina-Inspired Lightweight Spiking Convolutional Neural Network for Single-Image Dehazing [[paper](https://ieeexplore.ieee.org/document/10695026)]



# 2023



## ICCV-2023



- Efficient Converted Spiking Neural Network for 3D and 2D Classification [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Lan_Efficient_Converted_Spiking_Neural_Network_for_3D_and_2D_Classification_ICCV_2023_paper.html)] [[paper with code](https://paperswithcode.com/paper/efficient-converted-spiking-neural-network)]



- Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Meng_Towards_Memory-_and_Time-Efficient_Backpropagation_for_Training_Spiking_Neural_Networks_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2302.14311)] [[paper with code](https://paperswithcode.com/paper/towards-memory-and-time-efficient)] [[code](https://github.com/qymeng94/sltt)]



- Membrane Potential Batch Normalization for Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Guo_Membrane_Potential_Batch_Normalization_for_Spiking_Neural_Networks_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2308.08359)] [[paper with code](https://paperswithcode.com/paper/membrane-potential-batch-normalization-for)] [[code](https://github.com/yfguo91/mpbn)]



- Deep Directly-Trained Spiking Neural Networks for Object Detection [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Su_Deep_Directly-Trained_Spiking_Neural_Networks_for_Object_Detection_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2307.11411)] [[paper with code](https://paperswithcode.com/paper/deep-directly-trained-spiking-neural-networks)] [[code](https://github.com/BICLab/EMS-YOLO)]



- Unleashing the Potential of Spiking Neural Networks with Dynamic Confidence [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Li_Unleashing_the_Potential_of_Spiking_Neural_Networks_with_Dynamic_Confidence_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2303.10276)] [[paper with code](https://paperswithcode.com/paper/unleashing-the-potential-of-spiking-neural-2)]



- Temporal-Coded Spiking Neural Networks with Dynamic Firing Threshold: Learning with Event-Driven Backpropagation [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Wei_Temporal-Coded_Spiking_Neural_Networks_with_Dynamic_Firing_Threshold_Learning_with_ICCV_2023_paper.html)] [[paper with code](https://paperswithcode.com/paper/temporal-coded-spiking-neural-networks-with)]



- Inherent Redundancy in Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Yao_Inherent_Redundancy_in_Spiking_Neural_Networks_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2308.08227)] [[paper with code](https://paperswithcode.com/paper/inherent-redundancy-in-spiking-neural)] [[code](https://github.com/biclab/asa-snn)]



- SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Wang_SSF_Accelerating_Training_of_Spiking_Neural_Networks_with_Stabilized_Spiking_ICCV_2023_paper.html)] [[paper with code](https://paperswithcode.com/paper/ssf-accelerating-training-of-spiking-neural)]



- RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Guo_RMP-Loss_Regularizing_Membrane_Potential_Distribution_for_Spiking_Neural_Networks_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2308.06787)] [[paper with code](https://paperswithcode.com/paper/rmp-loss-regularizing-membrane-potential)] [[code](https://github.com/yfguo91/mpbn)]



- Masked Spiking Transformer [[paper](https://openaccess.thecvf.com/content/ICCV2023/html/Wang_Masked_Spiking_Transformer_ICCV_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2210.01208)] [[paper with code](https://paperswithcode.com/paper/efficient-spiking-transformer-enabled-by)] [[code](https://github.com/bic-L/Masked-Spiking-Transformer)]



## CVPR-2023



- Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/CVPR2023/html/Bu_Rate_Gradient_Approximation_Attack_Threats_Deep_Spiking_Neural_Networks_CVPR_2023_paper.html)] [[paper with code](https://paperswithcode.com/paper/rate-gradient-approximation-attack-threats)] [[code](https://github.com/putshua/snn_attack_rga)]



- Constructing Deep Spiking Neural Networks From Artificial Neural Networks With Knowledge Distillation [[paper](https://openaccess.thecvf.com/content/CVPR2023/html/Xu_Constructing_Deep_Spiking_Neural_Networks_From_Artificial_Neural_Networks_With_CVPR_2023_paper.html)] [[arxiv](https://arxiv.org/abs/2304.05627)] [[paper with code](https://paperswithcode.com/paper/constructing-deep-spiking-neural-networks)]



- 1000 FPS HDR Video With a Spike-RGB Hybrid Camera [[paper](https://openaccess.thecvf.com/content/CVPR2023/html/Chang_1000_FPS_HDR_Video_With_a_Spike-RGB_Hybrid_Camera_CVPR_2023_paper.html)] [[paper with code](https://paperswithcode.com/paper/1000-fps-hdr-video-with-a-spike-rgb-hybrid)]



## NeurIPS-2023



- Evolving Connectivity for Recurrent Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/08f9de0232c0b485110237f6e6cf88f1-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2305.17650)] [[paper with code](https://paperswithcode.com/paper/evolving-connectivity-for-recurrent-spiking)] [[openreview](https://openreview.net/forum?id=30o4ARmfC3)]



- SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/0b443d358a391166d1fbf551fb53de02-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2312.17216)] [[paper with code](https://paperswithcode.com/paper/sparseprop-efficient-event-based-simulation-1)] [[code](https://github.com/rainerengelken/sparseprop)] [[openreview](https://openreview.net/forum?id=yzZbwQPkmP)]



- Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/0bcf9cf6ffe26bba3af99e18be0e1d8d-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2306.12045)] [[paper with code](https://paperswithcode.com/paper/temporal-conditioning-spiking-latent-variable)] [[openreview](https://openreview.net/forum?id=V4YeOvsQfu)]



- Meta-learning families of plasticity rules in recurrent spiking networks using simulation-based inference [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/2bdc2267c3d7d01523e2e17ac0a754f3-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=FLFasCFJNo)]



- Learning in the Presence of Low-dimensional Structure: A Spiked Random Matrix Perspective [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/38a1671ab0747b6ffe4d1c6ef117a3a9-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=HlIAoCHDWW)]



- Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/421f83663c02cdaec8c3c38337709989-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2305.14077)] [[paper with code](https://paperswithcode.com/paper/mind-the-spikes-benign-overfitting-of-kernels)] [[code](https://github.com/moritzhaas/mind-the-spikes)] [[openreview](https://openreview.net/forum?id=yjYwbZBJyl)]



- EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/65e876f6a98c6799d0b3145966dd73e2-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=OMDgOjdqoZ)]



- Spiking PointNet: Spiking Neural Networks for Point Clouds [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/8296d5800a8e68e58ad0472b393be80e-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2310.06232)] [[paper with code](https://paperswithcode.com/paper/spiking-pointnet-spiking-neural-networks-for)] [[code](https://github.com/dayongren/spiking-pointnet)] [[openreview](https://openreview.net/forum?id=Ev2XuqvJCy)]



- Parallel Spiking Neurons with High Efficiency and Ability to Learn Long-term Dependencies [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/a834ac3dfdb90da54292c2c932c997cc-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2304.12760)] [[paper with code](https://paperswithcode.com/paper/parallel-spiking-neurons-with-high-efficiency)] [[code](https://github.com/fangwei123456/parallel-spiking-neuron)] [[openreview](https://openreview.net/forum?id=rfTFJvTkr2)]



- Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/b8734840bf65c8facd619f5105c6acd0-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2401.03719)] [[paper with code](https://paperswithcode.com/paper/enhancing-adaptive-history-reserving-by-1)] [[openreview](https://openreview.net/forum?id=aGZp61S9Lj)]



- Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/b9f253c2758a323f9d2095f91de9a974-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2311.11390)] [[paper with code](https://paperswithcode.com/paper/addressing-the-speed-accuracy-simulation)] [[code](https://github.com/webstorms/blocks)] [[openreview](https://openreview.net/forum?id=Ht79ZTVMsn)]



- SEENN: Towards Temporal Spiking Early Exit Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/c801e68207da477bbc44182b9fac1129-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2304.01230)] [[paper with code](https://paperswithcode.com/paper/seenn-towards-temporal-spiking-early-exit-1)] [[code](https://github.com/intelligent-computing-lab-yale/seenn)] [[openreview](https://openreview.net/forum?id=mbaN0Y0QTw)]



- Spike-driven Transformer [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/ca0f5358dbadda74b3049711887e9ead-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2307.01694)] [[paper with code](https://paperswithcode.com/paper/spike-driven-transformer-1)] [[code](https://github.com/biclab/spike-driven-transformer)] [[openreview](https://openreview.net/forum?id=9FmolyOHi5)]



- SPQR: Controlling Q-ensemble Independence with Spiked Random Model for Reinforcement Learning [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/cdcaf772b4f8eda0385d0930517de64a-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2401.03137)] [[paper with code](https://paperswithcode.com/paper/spqr-controlling-q-ensemble-independence-with-1)] [[code](https://github.com/dohyeoklee/SPQR)] [[openreview](https://openreview.net/forum?id=q0sdoFIfNg)]



- Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/cde874a797a8300da693d5e412b7fdc0-Abstract-Conference.html)] [[paper with code](https://paperswithcode.com/paper/exploring-loss-functions-for-time-based)] [[code](https://github.com/zhuyaoyu/snn-temporal-training-losses)] [[openreview](https://openreview.net/forum?id=8IvW2k5VeA)]



- Bayesian nonparametric (non-)renewal processes for analyzing neural spike train variability [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/d6db7eb6245ec0c6e45f445956994143-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=qlJoo2y3gY)]



- Enhancing Motion Deblurring in High-Speed Scenes with Spike Streams [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/dead3d8ff3f9198e38a36a950ebbcafd-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=cAyLnMxiTl)]



- Trial matching: capturing variability with data-constrained spiking neural networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/ec702dd6e83b2113a43614685a7e2ac6-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2306.03603)] [[paper with code](https://paperswithcode.com/paper/trial-matching-capturing-variability-with)] [[code](https://github.com/epfl-lcn/pub-sourmpis2023-neurips)] [[openreview](https://openreview.net/forum?id=LAbxkhkjbD)]



- Optimal Algorithms for the Inhomogeneous Spiked Wigner Model [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/f0a6b46b0183a62a2db973014e3429f4-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2302.06665)] [[paper with code](https://paperswithcode.com/paper/optimal-algorithms-for-the-inhomogeneous)] [[openreview](https://openreview.net/forum?id=xNUmTRYtV1)]



- Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/f499387f191d6be56e68966181095878-Abstract-Conference.html)] [[paper with code](https://paperswithcode.com/paper/bypassing-spike-sorting-density-based)] [[code](https://github.com/yzhang511/density_decoding)] [[openreview](https://openreview.net/forum?id=tgQRMrsxht)]



- Neural Data Transformer 2: Multi-context Pretraining for Neural Spiking Activity [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/fe51de4e7baf52e743b679e3bdba7905-Abstract-Conference.html)] [[paper with code](https://paperswithcode.com/paper/neural-data-transformer-2-multi-context)] [[code](https://github.com/joel99/context_general_bci)] [[openreview](https://openreview.net/forum?id=CBBtMnlTGq)]



- Direct Training of SNN using Local Zeroth Order Method [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/3c5e64f26a97db6a2b0bbb788236431e-Abstract-Conference.html)] [[paper with code](https://paperswithcode.com/paper/direct-training-of-snn-using-local-zeroth)] [[code](https://github.com/bhaskarmukhoty/localzo)] [[openreview](https://openreview.net/forum?id=eTF3VDH2b6)]



- Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera [[paper](https://proceedings.neurips.cc/paper_files/paper/2023/hash/96810b6d4752abe7bfb91f234c51e9e6-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2307.06003)] [[paper with code](https://paperswithcode.com/paper/unsupervised-optical-flow-estimation-with)] [[openreview](https://openreview.net/forum?id=7gbjsgcN5p)]



- SEENN: Towards Temporal Spiking Early-Exit Neural Networks [[paper](https://arxiv.org/abs/2304.01230)]



## AAAI-2023



- Reducing ANN-SNN Conversion Error through Residual Membrane Potential [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25071)] [[arxiv](https://arxiv.org/abs/2302.02091)] [[paper with code](https://paperswithcode.com/paper/reducing-ann-snn-conversion-error-through)] [[code](https://github.com/hzc1208/ANN2SNN_SRP)]



- Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25073)] [[arxiv](https://arxiv.org/abs/2303.06060)] [[paper with code](https://paperswithcode.com/paper/deep-spiking-neural-networks-with-high)] [[code](https://github.com/grasshlw/snn-neural-similarity)]



- ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25079)] [[arxiv](https://arxiv.org/abs/2306.03693)] [[paper with code](https://paperswithcode.com/paper/esl-snns-an-evolutionary-structure-learning)]



- Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25081)] [[arxiv](https://arxiv.org/abs/2302.01194)] [[paper with code](https://paperswithcode.com/paper/complex-dynamic-neurons-improved-spiking)] [[code](https://github.com/MingLunHan/CIF-PyTorch)]



- Learning Temporal-Ordered Representation for Spike Streams Based on Discrete Wavelet Transforms [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25085)]



- SVFI: Spiking-Based Video Frame Interpolation for High-Speed Motion [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25393)]



- Exploring Temporal Information Dynamics in Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/26002)] [[arxiv](https://arxiv.org/abs/2211.14406)] [[paper with code](https://paperswithcode.com/paper/exploring-temporal-information-dynamics-in)] [[code](https://github.com/intelligent-computing-lab-yale/exploring-temporal-information-dynamics-in-spiking-neural-networks)]



- Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/26034)] [[arxiv](https://arxiv.org/abs/2208.10364)] [[paper with code](https://paperswithcode.com/paper/scaling-up-dynamic-graph-representation)] [[code](https://github.com/edisonleeeee/spikenet)]



- Self-Supervised Joint Dynamic Scene Reconstruction and Optical Flow Estimation for Spiking Camera [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25108)]



- Learning to Super-resolve Dynamic Scenes for Neuromorphic Spike Camera [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25468)]



- Astromorphic Self-Repair of Neuromorphic Hardware Systems [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/25947)]



## ICML-2023



- Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks [[paper](https://proceedings.mlr.press/v202/deng23d.html)]



- Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains [[paper](https://proceedings.mlr.press/v202/dowling23a.html)] [[arxiv](https://arxiv.org/abs/2306.01802)] [[paper with code](https://paperswithcode.com/paper/linear-time-gps-for-inferring-latent)]



- Adaptive Smoothing Gradient Learning for Spiking Neural Networks [[paper](https://proceedings.mlr.press/v202/wang23j.html)] [[openreview](https://openreview.net/forum?id=s5NL0rQ31zJ)]



- A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates [[paper](https://proceedings.mlr.press/v202/jiang23a.html)] [[openreview](https://openreview.net/forum?id=83piwkGNzOP)]



## ICLR-2023



- Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes [[paper](https://iclr.cc/virtual/2023/poster/12118)] [[arxiv](https://arxiv.org/abs/2302.10685)] [[paper with code](https://paperswithcode.com/paper/bridging-the-gap-between-anns-and-snns-by)] [[code](https://github.com/hzc1208/ann2snn_cos)] [[openreview](https://openreview.net/forum?id=PFbzoWZyZRX)]



- Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles [[paper](https://iclr.cc/virtual/2023/poster/11083)] [[arxiv](https://arxiv.org/abs/2302.11618)] [[paper with code](https://paperswithcode.com/paper/heterogeneous-neuronal-and-synaptic-dynamics)] [[openreview](https://openreview.net/forum?id=QIRtAqoXwj)]



- Spiking Convolutional Neural Networks for Text Classification [[paper](https://iclr.cc/virtual/2023/poster/11720)] [[openreview](https://openreview.net/forum?id=pgU3k7QXuz0)]



- Spikformer: When Spiking Neural Network Meets Transformer [[paper](https://iclr.cc/virtual/2023/poster/12139)] [[arxiv](https://arxiv.org/abs/2209.15425)] [[paper with code](https://paperswithcode.com/paper/spikformer-when-spiking-neural-network-meets)] [[code](https://github.com/zk-zhou/spikformer)] [[openreview](https://openreview.net/forum?id=frE4fUwz_h)]



## IJCAI-2023



- Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2023/334)] [[arxiv](https://arxiv.org/abs/2308.04749)] [[paper with code](https://paperswithcode.com/paper/enhancing-efficient-continual-learning-with)] [[code](https://github.com/braincog-x/brain-cog)]



- Learnable Surrogate Gradient for Direct Training Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2023/335)]



- A Low Latency Adaptive Coding Spike Framework for Deep Reinforcement Learning [[paper](https://www.ijcai.org/proceedings/2023/340)] [[arxiv](https://arxiv.org/abs/2211.11760)]



- Spatial-Temporal Self-Attention for Asynchronous Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2023/344)]



- Spike Count Maximization for Neuromorphic Vision Recognition [[paper](https://www.ijcai.org/proceedings/2023/473)]



- A New ANN-SNN Conversion Method with High Accuracy, Low Latency and Good Robustness [[paper](https://www.ijcai.org/proceedings/2023/342)]



## ICASSP-2023



- Joint ANN-SNN Co-training for Object Localization and Image Segmentation [[paper](https://arxiv.org/abs/2303.12738)]



- Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition [[paper](https://arxiv.org/abs/2302.08607)]



- Training Robust Spiking Neural Networks with ViewPoint Transform and SpatioTemporal Stretching [[paper](https://arxiv.org/abs/2303.07609)]



- In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision [[paper](https://ieeexplore.ieee.org/document/10094902)]



- Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neurons [[paper](https://ieeexplore.ieee.org/document/10096958)]



- Training Robust Spiking Neural Networks on Neuromorphic Data with Spatiotemporal Fragments [[paper](https://ieeexplore.ieee.org/document/10096951)]



- Leveraging Sparsity with Spiking Recurrent Neural Networks for Energy-Efficient Keyword Spotting [[paper](https://ieeexplore.ieee.org/document/10097174)]



## IJCNN-2023



- Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Prediction [[paper](https://arxiv.org/abs/2304.04697)]



- Low Precision Quantization-aware Training in Spiking Neural Networks with Differentiable Quantization Function [[paper](https://arxiv.org/abs/2305.19295)]



## PAMI-2023



- Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN [[paper](https://arxiv.org/abs/2305.19868)] [[code](https://github.com/yangfan-hu/fast-snn)]



- Attention Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/10032591)] [[code](https://github.com/BICLab/Attention-SNN)]



- CQ+ Training: Minimizing Accuracy Loss in Conversion From Convolutional Neural Networks to Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/10152465)]



## TNNLS-2023



- Attention-Based Deep Spiking Neural Networks for Temporal Credit Assignment Problems [[paper](https://ieeexplore.ieee.org/document/10038509)] 



- Effective Active Learning Method for Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/10081108)]



- Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey [[paper](https://ieeexplore.ieee.org/document/10097504)]



## Neural Networks-2023



- SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks [[paper](https://doi.org/10.1016/j.neunet.2023.01.026)]



# 2022 



## CVPR-2022



- Spiking Transformers for Event-Based Single Object Tracking [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Zhang_Spiking_Transformers_for_Event-Based_Single_Object_Tracking_CVPR_2022_paper.html)] [[paper with code](https://paperswithcode.com/paper/spiking-transformers-for-event-based-single)]



- Brain-Inspired Multilayer Perceptron With Spiking Neurons [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Li_Brain-Inspired_Multilayer_Perceptron_With_Spiking_Neurons_CVPR_2022_paper.html)] [[arxiv](https://arxiv.org/abs/2203.14679)] [[paper with code](https://paperswithcode.com/paper/brain-inspired-multilayer-perceptron-with)] [[code](https://github.com/huawei-noah/Efficient-AI-Backbones)]



- Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Meng_Training_High-Performance_Low-Latency_Spiking_Neural_Networks_by_Differentiation_on_Spike_CVPR_2022_paper.html)] [[arxiv](https://arxiv.org/abs/2205.00459)] [[paper with code](https://paperswithcode.com/paper/training-high-performance-low-latency-spiking)] [[code](https://github.com/qymeng94/dsr)]



- RecDis-SNN: Rectifying Membrane Potential Distribution for Directly Training Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Guo_RecDis-SNN_Rectifying_Membrane_Potential_Distribution_for_Directly_Training_Spiking_Neural_CVPR_2022_paper.html)] [[paper with code](https://paperswithcode.com/paper/recdis-snn-rectifying-membrane-potential)]



- Event-Based Video Reconstruction via Potential-Assisted Spiking Neural Network [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Zhu_Event-Based_Video_Reconstruction_via_Potential-Assisted_Spiking_Neural_Network_CVPR_2022_paper.html)] [[arxiv](https://arxiv.org/abs/2201.10943)] [[paper with code](https://paperswithcode.com/paper/event-based-video-reconstruction-via)] [[code](https://github.com/LinZhu111/EVSNN)]



- Optical Flow Estimation for Spiking Camera [[paper](https://openaccess.thecvf.com/content/CVPR2022/html/Hu_Optical_Flow_Estimation_for_Spiking_Camera_CVPR_2022_paper.html)] [[arxiv](https://arxiv.org/abs/2110.03916)] [[paper with code](https://paperswithcode.com/paper/scflow-optical-flow-estimation-for-spiking)] [[code](https://github.com/acnext/optical-flow-for-spiking-camera)]



## ECCV-2022



- Spike Transformer: Monocular Depth Estimation for Spiking Camera [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/3125_ECCV_2022_paper.php)]



- Neuromorphic Data Augmentation for Training Spiking Neural Networks [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/601_ECCV_2022_paper.php)] [[arxiv](https://arxiv.org/abs/2203.06145)] [[paper with code](https://paperswithcode.com/paper/neuromorphic-data-augmentation-for-training)] [[code](https://github.com/intelligent-computing-lab-yale/nda_snn)]



- Reducing Information Loss for Spiking Neural Networks [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/88_ECCV_2022_paper.php)] [[arxiv](https://arxiv.org/abs/2307.04356)]



- Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6421_ECCV_2022_paper.php)]



- Real Spike: Learning Real-Valued Spikes for Spiking Neural Networks [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/6623_ECCV_2022_paper.php)] [[arxiv](https://arxiv.org/abs/2210.06686)] [[paper with code](https://paperswithcode.com/paper/real-spike-learning-real-valued-spikes-for)] [[code](https://github.com/yfguo91/Real-Spike)]



- Exploring Lottery Ticket Hypothesis in Spiking Neural Networks [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/7345_ECCV_2022_paper.php)] [[arxiv](https://arxiv.org/abs/2207.01382)] [[paper with code](https://paperswithcode.com/paper/lottery-ticket-hypothesis-for-spiking-neural)] [[code](https://github.com/intelligent-computing-lab-yale/exploring-lottery-ticket-hypothesis-in-snns)]



- Neural Architecture Search for Spiking Neural Networks [[paper](https://www.ecva.net/papers/eccv_2022/papers_ECCV/html/599_ECCV_2022_paper.php)] [[arxiv](https://arxiv.org/abs/2201.10355)] [[paper with code](https://paperswithcode.com/paper/neural-architecture-search-for-spiking-neural)] [[code](https://github.com/intelligent-computing-lab-yale/neural-architecture-search-for-spiking-neural-networks)]



- Lottery Ticket Hypothesis for Spiking Neural Networks [[paper](https://arxiv.org/abs/2207.01382)]



## NeurIPS-2022



- IM-Loss: Information Maximization Loss for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/010c5ba0cafc743fece8be02e7adb8dd-Abstract-Conference.html)] [[paper with code](https://paperswithcode.com/paper/im-loss-information-maximization-loss-for)] [[openreview](https://openreview.net/forum?id=Jw34v_84m2b)]



- Biologically Inspired Dynamic Thresholds for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/2858f8c8683aaa8c12d487354cf328dc-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2206.04426)] [[openreview](https://openreview.net/forum?id=1bE24ZURBqm)]



- Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/2c625366ae28066fcb1827b44517d674-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=cPVuuk1lZb3)]



- Learning Optical Flow from Continuous Spike Streams [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/33951c28630e48c441cb59db356f2037-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=3vYkhJIty7E)]



- Toward Robust Spiking Neural Network Against Adversarial Perturbation [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/42bc612558891859b1b8717051f2c7b0-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2205.01625)] [[paper with code](https://paperswithcode.com/paper/toward-robust-spiking-neural-network-against)] [[openreview](https://openreview.net/forum?id=Ncyc0JS7Q16)]



- Training Spiking Neural Networks with Local Tandem Learning [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/523caec7832a47fb19b8471dbfeec471-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2210.04532)] [[paper with code](https://paperswithcode.com/paper/training-spiking-neural-networks-with-local)] [[code](https://github.com/aries231/local_tandem_learning_rule)] [[openreview](https://openreview.net/forum?id=nC8VC8gVGPo)]



- Theoretically Provable Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/7abbcb05a5d55157ede410bb718e32d7-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=I0CiI7Oyp1E)]



- Bayesian Clustering of Neural Spiking Activity Using a Mixture of Dynamic Poisson Factor Analyzers [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/7b39f4512a2e3899edcc59c7501f3cd4-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=C0VKVmhlKgb)]



- Biologically plausible solutions for spiking networks with efficient coding [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/820c61a0cd419163ccbd2c33b268816e-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2210.07069)] [[paper with code](https://paperswithcode.com/paper/biologically-plausible-solutions-for-spiking)] [[openreview](https://openreview.net/forum?id=zdmYnIRXvKS)]



- Online Training Through Time for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/82846e19e6d42ebfd4ace4361def29ae-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2210.04195)] [[paper with code](https://paperswithcode.com/paper/online-training-through-time-for-spiking)] [[code](https://github.com/pkuxmq/ottt-snn)] [[openreview](https://openreview.net/forum?id=Siv3nHYHheI)]



- Natural gradient enables fast sampling in spiking neural networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/8a0fd48510590071e3c129a79b8b8527-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=Yopob26XjmL)]



- Mesoscopic modeling of hidden spiking neurons [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/953e742190ca02fc8f9f710052f2fead-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2205.13493)] [[paper with code](https://paperswithcode.com/paper/mesoscopic-modeling-of-hidden-spiking-neurons)] [[code](https://github.com/epfl-lcn/neulvm)] [[openreview](https://openreview.net/forum?id=cYPja_wj9d)]



- SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/9cf904c86cc5f9ac95646c07d2cfa241-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=xwBdjfKt7_W)]



- Differentiable hierarchical and surrogate gradient search for spiking neural networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/9e8c2895db691eaab85af37bddee75aa-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=Lr2Z85cdvB)]



- LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5fd95d6b16d3172e307103a97f19e1b-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=BbaSRgUHW3)]



- Training Spiking Neural Networks with Event-driven Backpropagation [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/c4e5f4de1b3cfc838eec6484d0b85378-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=d4JmP1T45WE)]



- Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/cba76ef96c4cd625631ab4d33285b045-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2211.06027)] [[paper with code](https://paperswithcode.com/paper/dance-of-snn-and-ann-solving-binding-problem)] [[code](https://github.com/monstersecond/dasbe)] [[openreview](https://openreview.net/forum?id=-yiZR4_Xhh)]



- GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/cfa8440d500a6a6867157dfd4eaff66e-Abstract-Conference.html)] [[arxiv](https://arxiv.org/abs/2210.13768)] [[paper with code](https://paperswithcode.com/paper/glif-a-unified-gated-leaky-integrate-and-fire)] [[code](https://github.com/ikarosy/gated-lif)] [[openreview](https://openreview.net/forum?id=UmFSx2c4ubT)]



- Temporal Effective Batch Normalization in Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2022/hash/de2ad3ed44ee4e675b3be42aa0b615d0-Abstract-Conference.html)] [[openreview](https://openreview.net/forum?id=fLIgyyQiJqz)]



- The computational and learning benefits of Daleian neural networks [[paper](https://openreview.net/forum?id=ckQvYXizgd1)]



- STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers [[paper](https://openreview.net/forum?id=iUOUnyS6uTf)]



## AAAI-2022



- Optimized Potential Initialization for Low-Latency Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/19874)] [[arxiv](https://arxiv.org/abs/2202.01440)] [[paper with code](https://paperswithcode.com/paper/optimized-potential-initialization-for-low)]



- Multi-Sacle Dynamic Coding Improved Spiking Actor Network for Reinforcement Learning [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/19879)]



- PrivateSNN: Privacy-Preserving Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/20005)] [[arxiv](https://arxiv.org/abs/2104.03414)] [[paper with code](https://paperswithcode.com/paper/privatesnn-fully-privacy-preserving-spiking)]



- SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/20061)]



- Fully Spiking Variational Autoencoder [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/20665)] [[arxiv](https://arxiv.org/abs/2110.00375)] [[paper with code](https://paperswithcode.com/paper/fully-spiking-variational-autoencoder)] [[code](https://github.com/kamata1729/FullySpikingVAE)]



- Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/20771)] [[arxiv](https://arxiv.org/abs/2109.01905)] [[paper with code](https://paperswithcode.com/paper/spiking-neural-networks-with-improved)] [[code](https://github.com/wponghiran/imp-snns-for-sl)]



- Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation [[paper](https://arxiv.org/abs/2109.04871)] [[code](https://github.com/ruizhao26/ste-flownet)]



## ICASSP-2022



- Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks [[paper](https://arxiv.org/abs/2205.02115)]



- Gradual Surrogate Gradient Learning in Deep Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/9746774)]



- T-NGA: Temporal Network Grafting Algorithm for Learning to Process Spiking Audio Sensor Events [[paper](https://ieeexplore.ieee.org/document/9747093)]



- Modeling The Detection Capability Of High-Speed Spiking Cameras [[paper](https://ieeexplore.ieee.org/document/9747018)]



- DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/9746566)]



- Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization [[paper](https://ieeexplore.ieee.org/document/9746375)]



- Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? [[paper](https://ieeexplore.ieee.org/document/9747906)]



- Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration [[paper](https://ieeexplore.ieee.org/document/9746157)]



- Event-Based Multimodal Spiking Neural Network with Attention Mechanism [[paper](https://ieeexplore.ieee.org/document/9746865)]



- A Hybrid Learning Framework for Deep Spiking Neural Networks with One-Spike Temporal Coding [[paper](https://ieeexplore.ieee.org/document/9746792)]



- Supervised Training of Siamese Spiking Neural Networks with Earth Mover's Distance [[paper](https://ieeexplore.ieee.org/document/9746630)]



- A Time Encoding Approach to Training Spiking Neural Networks [[paper](https://ieeexplore.ieee.org/document/9746319)]



## ICML-2022



- State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks [[paper](https://proceedings.mlr.press/v162/chen22ac.html)]



- AutoSNN: Towards Energy-Efficient Spiking Neural Networks [[paper](https://proceedings.mlr.press/v162/na22a.html)] [[arxiv](https://arxiv.org/abs/2201.12738)] [[paper with code](https://paperswithcode.com/paper/autosnn-towards-energy-efficient-spiking)] [[code](https://github.com/nabk89/autosnn)]



- Scalable Spike-and-Slab [[paper](https://proceedings.mlr.press/v162/biswas22a.html)] [[arxiv](https://arxiv.org/abs/2204.01668)] [[paper with code](https://paperswithcode.com/paper/scalable-spike-and-slab)] [[code](https://github.com/niloyb/scalespikeslab)]



- Neural Network Poisson Models for Behavioural and Neural Spike Train Data [[paper](https://proceedings.mlr.press/v162/khajehnejad22a.html)]



## IJCAI-2022



- Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes [[paper](https://www.ijcai.org/proceedings/2022/345)] [[arxiv](https://arxiv.org/abs/2204.13271)] [[paper with code](https://paperswithcode.com/paper/efficient-and-accurate-conversion-of-spiking)] [[code](https://github.com/brain-inspired-cognitive-engine/conversion_burst)]



- Spiking Graph Convolutional Networks [[paper](https://www.ijcai.org/proceedings/2022/338)] [[arxiv](https://arxiv.org/abs/2205.02767)] [[paper with code](https://paperswithcode.com/paper/spiking-graph-convolutional-networks-1)] [[code](https://github.com/zulunzhu/spikinggcn)]



- Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion [[paper](https://www.ijcai.org/proceedings/2022/347)] [[code](https://github.com/ppppps/ANN2SNNConversion_SNM_NeuronNorm)]



- Self-Supervised Mutual Learning for Dynamic Scene Reconstruction of Spiking Camera [[paper](https://www.ijcai.org/proceedings/2022/396)]



- Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2022/343)] [[arxiv](https://arxiv.org/abs/2210.06386)] [[paper with code](https://paperswithcode.com/paper/multi-level-firing-with-spiking-ds-resnet)] [[code](https://github.com/langfengq/mlf-dsresnet)]



## ICLR-2022 



- Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks [[paper](https://iclr.cc/virtual/2022/poster/5899)] [[arxiv](https://arxiv.org/abs/2303.04347)] [[paper with code](https://paperswithcode.com/paper/optimal-ann-snn-conversion-for-high-accuracy-1)] [[code](https://github.com/putshua/SNN_conversion_QCFS)] [[openreview](https://openreview.net/forum?id=7B3IJMM1k_M)]



- Spike-inspired rank coding for fast and accurate recurrent neural networks [[paper](https://iclr.cc/virtual/2022/poster/6217)] [[arxiv](https://arxiv.org/abs/2110.02865)] [[paper with code](https://paperswithcode.com/paper/spike-inspired-rank-coding-for-fast-and)] [[code](https://github.com/NeuromorphicComputing/RankCoding)] [[openreview](https://openreview.net/forum?id=iMH1e5k7n3L)]



- Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods [[paper](https://iclr.cc/virtual/2022/poster/6640)] [[paper with code](https://paperswithcode.com/paper/sequence-approximation-using-feedforward)] [[openreview](https://openreview.net/forum?id=bp-LJ4y_XC)]



- Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting [[paper](https://iclr.cc/virtual/2022/poster/6033)] [[arxiv](https://arxiv.org/abs/2202.11946)] [[paper with code](https://paperswithcode.com/paper/temporal-efficient-training-of-spiking-neural-1)] [[code](https://github.com/gus-lab/temporal_efficient_training)] [[openreview](https://openreview.net/forum?id=_XNtisL32jv)]



## IJCNN-2022



- Event-Driven Tactile Learning with Location Spiking Neurons [[paper](https://arxiv.org/abs/2209.01080)] [[code](https://github.com/pkang2017/tactilelocneurons)]



- Spiking Approximations of the MaxPooling Operation in Deep SNNs [[paper](https://arxiv.org/abs/2205.07076)] [[code](https://github.com/R-Gaurav/SpikingMaxPooling)]



- Spikemax: Spike-based Loss Methods for Classification [[paper](https://arxiv.org/abs/2205.09845)]



- Object Detection with Spiking Neural Networks on Automotive Event Data [[paper](https://arxiv.org/abs/2205.04339)] [[code](https://github.com/loiccordone/object-detection-with-spiking-neural-networks)]



## NEURAL COMPUTATION



- Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling [[paper](https://direct.mit.edu/neco/article-abstract/34/5/1170/109666/Training-Deep-Convolutional-Spiking-Neural?redirectedFrom=fulltext)]



## Neural Networks-2022



- Modeling learnable electrical synapse for high precision spatio-temporal recognition  [[paper](https://www.sciencedirect.com/science/article/pii/S0893608022000399?via%3Dihub)]



## IEEE TCYB (IEEE Transactions on Cybernetics)



- Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning [[paper](https://ieeexplore.ieee.org/document/9082167)]



# 2021



## NeurIPS-2021



- Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/39d4b545fb02556829aab1db805021c3-Abstract.html)] [[arxiv](https://arxiv.org/abs/2106.01862)] [[paper with code](https://paperswithcode.com/paper/self-supervised-learning-of-event-based)] [[openreview](https://openreview.net/forum?id=MySjw6CHPa4)]



- Sparse Spiking Gradient Descent [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/61f2585b0ebcf1f532c4d1ec9a7d51aa-Abstract.html)] [[arxiv](https://arxiv.org/abs/2105.08810)] [[paper with code](https://paperswithcode.com/paper/sparse-spiking-gradient-descent)] [[code](https://github.com/npvoid/SparseSpikingBackprop)] [[openreview](https://openreview.net/forum?id=aLE2sEtMNXv)]



- A universal probabilistic spike count model reveals ongoing modulation of neural variability [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/6f5216f8d89b086c18298e043bfe48ed-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/a-universal-probabilistic-spike-count-model)] [[openreview](https://openreview.net/forum?id=6ZdqOpE_UVF)]



- Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium State [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/79a49b3e3762632813f9e35f4ba53d6c-Abstract.html)] [[arxiv](https://arxiv.org/abs/2109.14247)] [[paper with code](https://paperswithcode.com/paper/training-feedback-spiking-neural-networks-by)] [[code](https://github.com/pkuxmq/ide-fsnn)] [[openreview](https://openreview.net/forum?id=f2Llmm_z5Sm)]



- Probabilistic Tensor Decomposition of Neural Population Spiking Activity [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/859b755563f548d008f936906a959c8f-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/probabilistic-tensor-decomposition-of-neural)] [[code](https://github.com/hugosou/vbgcp)] [[openreview](https://openreview.net/forum?id=1bBF5Zq1YHz)]



- Learning to Time-Decode in Spiking Neural Networks Through the Information Bottleneck [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/8da57fac3313174128cc5f13328d4573-Abstract.html)] [[arxiv](https://arxiv.org/abs/2106.01177)] [[paper with code](https://paperswithcode.com/paper/learning-to-time-decode-in-spiking-neural)] [[openreview](https://openreview.net/forum?id=Fw0IQgaGlhh)]



- Fitting summary statistics of neural data with a differentiable spiking network simulator [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/9a32ff36c65e8ba30915a21b7bd76506-Abstract.html)] [[arxiv](https://arxiv.org/abs/2106.10064)] [[paper with code](https://paperswithcode.com/paper/fitting-summary-statistics-of-neural-data)] [[code](https://github.com/epfl-lcn/pub-bellec-wang-2021-sample-and-measure)] [[openreview](https://openreview.net/forum?id=9DEAT9pDiN)]



- Deep Residual Learning in Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/afe434653a898da20044041262b3ac74-Abstract.html)] [[arxiv](https://arxiv.org/abs/2102.04159)] [[paper with code](https://paperswithcode.com/paper/spike-based-residual-blocks)] [[code](https://github.com/fangwei123456/Spike-Element-Wise-ResNet)]



- Three-dimensional spike localization and improved motion correction for Neuropixels recordings [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/b950ea26ca12daae142bd74dba4427c8-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/three-dimensional-spike-localization-and)] [[openreview](https://openreview.net/forum?id=ohfi44BZPC4)]



- Differentiable Spike: Rethinking Gradient-Descent for Training Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2021/hash/c4ca4238a0b923820dcc509a6f75849b-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/differentiable-spike-rethinking-gradient)] [[openreview](https://openreview.net/forum?id=H4e7mBnC9f0)]



## CVPR-2021



- Spk2ImgNet: Learning To Reconstruct Dynamic Scene From Continuous Spike Stream [[paper](https://openaccess.thecvf.com/content/CVPR2021/html/Zhao_Spk2ImgNet_Learning_To_Reconstruct_Dynamic_Scene_From_Continuous_Spike_Stream_CVPR_2021_paper.html)] [[paper with code](https://paperswithcode.com/paper/spk2imgnet-learning-to-reconstruct-dynamic)]



## ICLR-2021



- Efficient Inference of Flexible Interaction in Spiking-neuron Networks [[paper](https://iclr.cc/virtual/2021/poster/2648)] [[arxiv](https://arxiv.org/abs/2006.12845)] [[paper with code](https://paperswithcode.com/paper/efficient-inference-of-nonparametric)] [[openreview](https://openreview.net/forum?id=aGfU_xziEX8)]



- Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks [[paper](https://iclr.cc/virtual/2021/poster/2644)] [[arxiv](https://arxiv.org/abs/2103.00476)] [[paper with code](https://paperswithcode.com/paper/optimal-conversion-of-conventional-artificial-1)] [[code](https://github.com/Jackn0/snn_optimal_conversion_pipeline)] [[openreview](https://openreview.net/forum?id=FZ1oTwcXchK)]



## ICCV-2021



- HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training With Crafted Input Noise [[paper](https://openaccess.thecvf.com/content/ICCV2021/html/Kundu_HIRE-SNN_Harnessing_the_Inherent_Robustness_of_Energy-Efficient_Deep_Spiking_Neural_ICCV_2021_paper.html)] [[arxiv](https://arxiv.org/abs/2110.11417)] [[paper with code](https://paperswithcode.com/paper/hire-snn-harnessing-the-inherent-robustness-1)] [[code](https://github.com/ksouvik52/hiresnn2021)]



- DCT-SNN: Using DCT To Distribute Spatial Information Over Time for Low-Latency Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2021/html/Garg_DCT-SNN_Using_DCT_To_Distribute_Spatial_Information_Over_Time_for_ICCV_2021_paper.html)] [[arxiv](https://arxiv.org/abs/2010.01795)] [[paper with code](https://paperswithcode.com/paper/dct-snn-using-dct-to-distribute-spatial)]



- Super Resolve Dynamic Scene From Continuous Spike Streams [[paper](https://openaccess.thecvf.com/content/ICCV2021/html/Zhao_Super_Resolve_Dynamic_Scene_From_Continuous_Spike_Streams_ICCV_2021_paper.html)] [[paper with code](https://paperswithcode.com/paper/super-resolve-dynamic-scene-from-continuous)]



- Incorporating Learnable Membrane Time Constant To Enhance Learning of Spiking Neural Networks [[paper](https://openaccess.thecvf.com/content/ICCV2021/html/Fang_Incorporating_Learnable_Membrane_Time_Constant_To_Enhance_Learning_of_Spiking_ICCV_2021_paper.html)] [[arxiv](https://arxiv.org/abs/2007.05785)] [[paper with code](https://paperswithcode.com/paper/leaky-integrate-and-fire-spiking-neuron-with)] [[code](https://github.com/fangwei123456/Parametric-Leaky-Integrate-and-Fire-Spiking-Neuron)]



- Temporal-Wise Attention Spiking Neural Networks for Event Streams Classification [[paper](https://openaccess.thecvf.com/content/ICCV2021/html/Yao_Temporal-Wise_Attention_Spiking_Neural_Networks_for_Event_Streams_Classification_ICCV_2021_paper.html)] [[arxiv](https://arxiv.org/abs/2107.11711)] [[paper with code](https://paperswithcode.com/paper/temporal-wise-attention-spiking-neural)]



## ICML-2021



- Detection of Signal in the Spiked Rectangular Models [[paper](https://proceedings.mlr.press/v139/jung21a.html)] [[arxiv](https://arxiv.org/abs/2104.13517)] [[paper with code](https://paperswithcode.com/paper/detection-of-signal-in-the-spiked-rectangular)]



- A Differentiable Point Process with Its Application to Spiking Neural Networks [[paper](https://proceedings.mlr.press/v139/kajino21a.html)] [[arxiv](https://arxiv.org/abs/2106.00901)] [[paper with code](https://paperswithcode.com/paper/a-differentiable-point-process-with-its)] [[code](https://github.com/ibm-research-tokyo/diffsnn)]



- A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration [[paper](https://proceedings.mlr.press/v139/li21d.html)] [[arxiv](https://arxiv.org/abs/2106.06984)] [[paper with code](https://paperswithcode.com/paper/a-free-lunch-from-ann-towards-efficient)] [[code](https://github.com/yhhhli/SNN_Calibration)]



- Backpropagated Neighborhood Aggregation for Accurate Training of Spiking Neural Networks [[paper](https://proceedings.mlr.press/v139/yang21n.html)] [[arxiv](https://arxiv.org/abs/2107.06861)] [[paper with code](https://paperswithcode.com/paper/backpropagated-neighborhood-aggregation-for)]



## IJCAI-2021



- Pruning of Deep Spiking Neural Networks through Gradient Rewiring [[paper](https://www.ijcai.org/proceedings/2021/236)] [[arxiv](https://arxiv.org/abs/2105.04916)] [[paper with code](https://paperswithcode.com/paper/pruning-of-deep-spiking-neural-networks)] [[code](https://github.com/Yanqi-Chen/Gradient-Rewiring)]



- Event-based Action Recognition Using Motion Information and Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2021/240)]



- Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2021/321)] [[arxiv](https://arxiv.org/abs/2105.11654)] [[paper with code](https://paperswithcode.com/paper/optimal-ann-snn-conversion-for-fast-and)] [[code](https://github.com/DingJianhao/OptSNNConvertion-RNL-RIL)]



- Exploiting Spiking Dynamics with Spatial-temporal Feature Normalization in Graph Learning [[paper](https://www.ijcai.org/proceedings/2021/441)] [[arxiv](https://arxiv.org/abs/2107.06865)] [[paper with code](https://paperswithcode.com/paper/exploiting-spiking-dynamics-with-spatial)]



## AAAI-2021



- Deep Spiking Neural Network with Neural Oscillation and Spike-Phase Information [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/16870)]



- Strategy and Benchmark for Converting Deep Q-Networks to Event-Driven Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/17180)] [[arxiv](https://arxiv.org/abs/2009.14456)] [[paper with code](https://paperswithcode.com/paper/strategy-and-benchmark-for-converting-deep-q)]



- Training Spiking Neural Networks with Accumulated Spiking Flow [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/17236)]



- Near Lossless Transfer Learning for Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/17265)]



- Going Deeper With Directly-Trained Larger Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/17320)] [[arxiv](https://arxiv.org/abs/2011.05280)] [[paper with code](https://paperswithcode.com/paper/going-deeper-with-directly-trained-larger)] [[code](https://github.com/thiswinex/STBP-simple)]



- Temporal-Coded Deep Spiking Neural Network with Easy Training and Robust Performance [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/17329)] [[arxiv](https://arxiv.org/abs/1909.10837)] [[paper with code](https://paperswithcode.com/paper/direct-training-based-spiking-convolutional)] [[code](https://github.com/zbs881314/Temporal-Coded-Deep-SNN)]



# 2020



## NeurIPS-2020



- Rescuing neural spike train models from bad MLE [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/186b690e29892f137b4c34cfa40a3a4d-Abstract.html)] [[arxiv](https://arxiv.org/abs/2010.12362)] [[paper with code](https://paperswithcode.com/paper/rescuing-neural-spike-train-models-from-bad)] [[code](https://github.com/diegoarri91/mmd-glm)]



- Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/33cf42b38bbcf1dd6ba6b0f0cd005328-Abstract.html)] [[arxiv](https://arxiv.org/abs/2006.08115)] [[paper with code](https://paperswithcode.com/paper/minimax-dynamics-of-optimally-balanced-1)] [[code](https://github.com/Pehlevan-Group/BalancedEIMinimax)]



- Estimating Rank-One Spikes from Heavy-Tailed Noise via Self-Avoiding Walks [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/3c0de3fec9ab8a3df01109251f137119-Abstract.html)] [[arxiv](https://arxiv.org/abs/2008.13735)] [[paper with code](https://paperswithcode.com/paper/estimating-rank-one-spikes-from-heavy-tailed)]



- Understanding spiking networks through convex optimization [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/64714a86909d401f8feb83e8c2d94b23-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/understanding-spiking-networks-through-convex)] [[code](https://github.com/machenslab/spikes)]



- Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/8bdb5058376143fa358981954e7626b8-Abstract.html)] [[arxiv](https://arxiv.org/abs/2002.10085)] [[paper with code](https://paperswithcode.com/paper/temporal-spike-sequence-learning-via)] [[code](https://github.com/stonezwr/TSSL-BP)]



- Point process models for sequence detection in high-dimensional neural spike trains [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/a5481cd6d7517aa3fc6476dc7d9019ab-Abstract.html)] [[arxiv](https://arxiv.org/abs/2010.04875)] [[paper with code](https://paperswithcode.com/paper/point-process-models-for-sequence-detection)] [[code](https://github.com/lindermanlab/PPSeq.jl)]



- Spike and slab variational Bayes for high dimensional logistic regression [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/a5bad363fc47f424ddf5091c8471480a-Abstract.html)] [[arxiv](https://arxiv.org/abs/2010.11665)] [[paper with code](https://paperswithcode.com/paper/spike-and-slab-variational-bayes-for-high)]



- All-or-nothing statistical and computational phase transitions in sparse spiked matrix estimation [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/aaa5ebec57257fa776a1990c2bd025c1-Abstract.html)] [[arxiv](https://arxiv.org/abs/2006.07971)] [[paper with code](https://paperswithcode.com/paper/all-or-nothing-statistical-and-computational)]



- Nonasymptotic Guarantees for Spiked Matrix Recovery with Generative Priors [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/ad62cfd33e3870262d6bf5331c1f13b0-Abstract.html)] [[arxiv](https://arxiv.org/abs/2006.07953)] [[paper with code](https://paperswithcode.com/paper/nonasymptotic-guarantees-for-low-rank-matrix)]



- Unifying Activation- and Timing-based Learning Rules for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2020/hash/e2e5096d574976e8f115a8f1e0ffb52b-Abstract.html)] [[arxiv](https://arxiv.org/abs/2006.02642)] [[paper with code](https://paperswithcode.com/paper/unifying-activation-and-timing-based-learning)] [[code](https://github.com/KyungsuKim42/ANTLR)]



## CVPR-2020



- Retina-Like Visual Image Reconstruction via Spiking Neural Model [[paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Zhu_Retina-Like_Visual_Image_Reconstruction_via_Spiking_Neural_Model_CVPR_2020_paper.html)] [[paper with code](https://paperswithcode.com/paper/retina-like-visual-image-reconstruction-via)]



- RMP-SNN: Residual Membrane Potential Neuron for Enabling Deeper High-Accuracy and Low-Latency Spiking Neural Network [[paper](https://openaccess.thecvf.com/content_CVPR_2020/html/Han_RMP-SNN_Residual_Membrane_Potential_Neuron_for_Enabling_Deeper_High-Accuracy_and_CVPR_2020_paper.html)] [[arxiv](https://arxiv.org/abs/2003.01811)] [[paper with code](https://paperswithcode.com/paper/rmp-snns-residual-membrane-potential-neuron)] [[code](https://github.com/facebookarchive/fb.resnet.torch)]



## ICLR-2020



- Spike-based causal inference for weight alignment [[paper](https://iclr.cc/virtual/2020/poster/1906)] [[arxiv](https://arxiv.org/abs/1910.01689)] [[paper with code](https://paperswithcode.com/paper/spike-based-causal-inference-for-weight-1)] [[code](https://github.com/nasiryahm/STDWI)] [[openreview](https://openreview.net/forum?id=rJxWxxSYvB)]



- SpikeGrad: An ANN-equivalent Computation Model for Implementing Backpropagation with Spikes [[paper](https://iclr.cc/virtual/2020/poster/1686)] [[arxiv](https://arxiv.org/abs/1906.00851)] [[paper with code](https://paperswithcode.com/paper/190600851)] [[openreview](https://openreview.net/forum?id=rkxs0yHFPH)]



- Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation [[paper](https://iclr.cc/virtual/2020/poster/1526)] [[arxiv](https://arxiv.org/abs/2005.01807)] [[paper with code](https://paperswithcode.com/paper/enabling-deep-spiking-neural-networks-with-1)] [[code](https://github.com/nitin-rathi/hybrid-snn-conversion)] [[openreview](https://openreview.net/forum?id=B1xSperKvH)]



## ECCV-2020



- Deep Spiking Neural Network: Energy Efficiency Through Time based Coding [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/1103_ECCV_2020_paper.php)]



- Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6736_ECCV_2020_paper.php)] [[arxiv](https://arxiv.org/abs/2003.06696)]



- Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-Linear Activations [[paper](https://www.ecva.net/papers/eccv_2020/papers_ECCV/html/6748_ECCV_2020_paper.php)] [[arxiv](https://arxiv.org/abs/2003.10399)]



## ICML-2020



- Efficient Non-conjugate Gaussian Process Factor Models for Spike Count Data using Polynomial Approximations [[paper](https://proceedings.mlr.press/v119/keeley20a.html)] [[arxiv](https://arxiv.org/abs/1906.03318)] [[paper with code](https://paperswithcode.com/paper/efficient-non-conjugate-gaussian-process)]



## IJCAI-2020



- LISNN: Improving Spiking Neural Networks with Lateral Interactions for Robust Object Recognition [[paper](https://www.ijcai.org/proceedings/2020/211)]



- Exploiting Neuron and Synapse Filter Dynamics in Spatial Temporal Learning of Deep Spiking Neural Network [[paper](https://www.ijcai.org/proceedings/2020/388)] [[arxiv](https://arxiv.org/abs/2003.02944)] [[paper with code](https://paperswithcode.com/paper/exploiting-neuron-and-synapse-filter-dynamics)] [[code](https://github.com/Snow-Crash/snn-iir)]



## AAAI-2020



- Deep Spiking Delayed Feedback Reservoirs and Its Application in Spectrum Sensing of MIMO-OFDM Dynamic Spectrum Sharing [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/5484)]



- Effective AER Object Classification Using Segmented Probability-Maximization Learning in Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/5486)] [[arxiv](https://arxiv.org/abs/2002.06199)] [[paper with code](https://paperswithcode.com/paper/effective-aer-object-classification-using)]



- Biologically Plausible Sequence Learning with Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/5487)] [[arxiv](https://arxiv.org/abs/1911.10943)] [[paper with code](https://paperswithcode.com/paper/biologically-plausible-sequence-learning-with)]



- New Efficient Multi-Spike Learning for Fast Processing and Robust Learning [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/5896)]



- Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detection [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/6787)] [[arxiv](https://arxiv.org/abs/1903.06530)] [[paper with code](https://paperswithcode.com/paper/spiking-yolo-spiking-neural-network-for-real)]



# 2019



## NeurIPS-2019



- The spiked matrix model with generative priors [[paper](https://proceedings.neurips.cc/paper_files/paper/2019/hash/2f3c6a4cd8af177f6456e7e51a916ff3-Abstract.html)] [[arxiv](https://arxiv.org/abs/1905.12385)] [[paper with code](https://paperswithcode.com/paper/the-spiked-matrix-model-with-generative)] [[code](https://github.com/sphinxteam/StructuredPrior_demo)]



- Enabling hyperparameter optimization in sequential autoencoders for spiking neural data [[paper](https://proceedings.neurips.cc/paper_files/paper/2019/hash/6948bd44c91acd2b54ecdd1b132f10fb-Abstract.html)] [[arxiv](https://arxiv.org/abs/1908.07896)] [[paper with code](https://paperswithcode.com/paper/190807896)] [[code](https://github.com/snel-repo/lfads-cd)]



- Scalable Spike Source Localization in Extracellular Recordings using Amortized Variational Inference [[paper](https://proceedings.neurips.cc/paper_files/paper/2019/hash/f12f2b34a0c3174269c19e21c07dee68-Abstract.html)] [[arxiv](https://arxiv.org/abs/1905.12375)] [[paper with code](https://paperswithcode.com/paper/scalable-spike-source-localization-in)] [[code](https://github.com/colehurwitz/vae_spike_localization)]



- Spike-Train Level Backpropagation for Training Deep Recurrent Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2019/hash/f42a37d114a480b6b57b60ea9a14a9d2-Abstract.html)] [[arxiv](https://arxiv.org/abs/1908.06378)] [[paper with code](https://paperswithcode.com/paper/spike-train-level-backpropagation-for)] [[code](https://github.com/stonezwr/ST-RSBP)]



- Who is Afraid of Big Bad Minima? Analysis of gradient-flow in spiked matrix-tensor models [[paper](https://proceedings.neurips.cc/paper_files/paper/2019/hash/fbad540b2f3b5638a9be9aa6a4d8e450-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/who-is-afraid-of-big-bad-minima-analysis-of-1)] [[code](https://github.com/sphinxteam/spiked_matrix-tensor_T0)]



## ICML-2019



- Weak Detection of Signal in the Spiked Wigner Model [[paper](https://proceedings.mlr.press/v97/chung19a.html)]



- Bayesian Joint Spike-and-Slab Graphical Lasso [[paper](https://proceedings.mlr.press/v97/li19h.html)] [[arxiv](https://arxiv.org/abs/1805.07051)] [[paper with code](https://paperswithcode.com/paper/bayesian-joint-spike-and-slab-graphical-lasso)] [[code](https://github.com/richardli/SSJGL)]



- Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models [[paper](https://proceedings.mlr.press/v97/mannelli19a.html)] [[arxiv](https://arxiv.org/abs/1902.00139)]



## IJCAI-2019



- STCA: Spatio-Temporal Credit Assignment with Delayed Feedback in Deep Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2019/189)]



- Fast and Accurate Classification with a Multi-Spike Learning Algorithm for Spiking Neurons [[paper](https://www.ijcai.org/proceedings/2019/200)]



## AAAI-2019



- Direct Training for Spiking Neural Networks: Faster, Larger, Better [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/3929)] [[arxiv](https://arxiv.org/abs/1809.05793)] [[paper with code](https://paperswithcode.com/paper/direct-training-for-spiking-neural-networks)]



- TDSNN: From Deep Neural Networks to Deep Spike Neural Networks with Temporal-Coding [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/3931)]



- MPD-AL: An Efficient Membrane Potential Driven Aggregate-Label Learning Algorithm for Spiking Neurons [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/3932)]



- Implementation of Boolean AND and OR Logic Gates with Biologically Reasonable Time Constants in Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/5147)]



# 2018



## NeurIPS-2018



- Gradient Descent for Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2018/hash/185e65bc40581880c4f2c82958de8cfe-Abstract.html)] [[arxiv](https://arxiv.org/abs/1706.04698)]



- Hybrid Macro/Micro Level Backpropagation for Training Deep Spiking Neural Networks [[paper](https://proceedings.neurips.cc/paper_files/paper/2018/hash/3fb04953d95a94367bb133f862402bce-Abstract.html)] [[arxiv](https://arxiv.org/abs/1805.07866)] [[paper with code](https://paperswithcode.com/paper/hybrid-macromicro-level-backpropagation-for)] [[code](https://github.com/jinyyy666/mm-bp-snn)]



- SLAYER: Spike Layer Error Reassignment in Time [[paper](https://proceedings.neurips.cc/paper_files/paper/2018/hash/82f2b308c3b01637c607ce05f52a2fed-Abstract.html)] [[arxiv](https://arxiv.org/abs/1810.08646)] [[paper with code](https://paperswithcode.com/paper/slayer-spike-layer-error-reassignment-in-time)] [[code](https://bitbucket.org/bamsumit/slayer)]



- Long short-term memory and Learning-to-learn in networks of spiking neurons [[paper](https://proceedings.neurips.cc/paper_files/paper/2018/hash/c203d8a151612acf12457e4d67635a95-Abstract.html)] [[arxiv](https://arxiv.org/abs/1803.09574)] [[paper with code](https://paperswithcode.com/paper/long-short-term-memory-and-learning-to-learn)] [[code](https://github.com/IGITUGraz/LSNN-official)]



- Temporal alignment and latent Gaussian process factor inference in population spike trains [[paper](https://proceedings.neurips.cc/paper_files/paper/2018/hash/d1ff1ec86b62cd5f3903ff19c3a326b2-Abstract.html)] [[paper with code](https://paperswithcode.com/paper/temporal-alignment-and-latent-gaussian)]



## ICLR-2018



- Temporally Efficient Deep Learning with Spikes [[paper](https://openreview.net/forum?id=HkZy-bW0-)] [[arxiv](https://arxiv.org/abs/1706.04159)] [[paper with code](https://paperswithcode.com/paper/temporally-efficient-deep-learning-with)] [[code](https://github.com/petered/pdnn)] [[openreview](https://openreview.net/forum?id=HkZy-bW0-)]



## ICML-2018



- Non-linear motor control by local learning in spiking neural networks [[paper](https://proceedings.mlr.press/v80/gilra18a.html)] [[arxiv](https://arxiv.org/abs/1712.10158)] [[paper with code](https://paperswithcode.com/paper/non-linear-motor-control-by-local-learning-in)] [[code](https://github.com/adityagilra/FOLLOWControl)]



## IJCAI-2018



- Jointly Learning Network Connections and Link Weights in Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2018/221)]



- CSNN: An Augmented Spiking based Framework with Perceptron-Inception [[paper](https://www.ijcai.org/proceedings/2018/228)]



- Brain-inspired Balanced Tuning for Spiking Neural Networks [[paper](https://www.ijcai.org/proceedings/2018/229)]



## AAAI-2018



- A Plasticity-Centric Approach to Train the Non-Differential Spiking Neural Networks [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/11317)]



- Learning Nonlinear Dynamics in Efficient, Balanced Spiking Networks Using Local Plasticity Rules [[paper](https://ojs.aaai.org/index.php/AAAI/article/view/11320)]



# Starchart



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