Awesome SNN Conference Paper

🔥 This repo collects summit papers, codes about Spiking Neural Networks for anyone who wants to do research on it. We are continuously improving the project. The part of 2022 is referenced in this.

🤗 Welcome anyone who is interested to contribute to the repo together !

• 2023
  • CVPR (IEEE Conference on Computer Vision and Pattern Recognition)
  • AAAI (Association for the Advancement of Artificial Intelligence)
  • ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing)
  • ICLR (International Conference on Learning Representations)
  • 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)
  • Neural Networks
• 2022
  • CVPR
  • ECCV
  • NeurIPS
  • AAAI
  • ICASSP
  • ICML
  • IJCAI
  • ICLR
  • IJCNN
  • NEURAL COMPUTATION
  • Neural Networks
  • IEEE TCYB (IEEE Transactions on Cybernetics)

2023

CVPR (IEEE Conference on Computer Vision and Pattern Recognition)

• Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks [paper] [code]

• Constructing Deep Spiking Neural Networks From Artificial Neural Networks With Knowledge Distillation [paper]

AAAI (Association for the Advancement of Artificial Intelligence)

• Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse [paper] [code]

• Exploring Temporal Information Dynamics in Spiking Neural Networks [paper] [code]

• Reducing ANN-SNN Conversion Error through Residual Membrane Potential [paper] [code]

ICASSP (IEEE International Conference on Acoustics, Speech and Signal Processing)

• Joint ANN-SNN Co-training for Object Localization and Image Segmentation [paper]

• Adaptive Axonal Delays in feedforward spiking neural networks for accurate spoken word recognition [paper]

• Training Robust Spiking Neural Networks with ViewPoint Transform and SpatioTemporal Stretching [paper]

• In-Sensor & Neuromorphic Computing Are all You Need for Energy Efficient Computer Vision [paper]

• Training Stronger Spiking Neural Networks with Biomimetic Adaptive Internal Association Neurons [paper]

• Training Robust Spiking Neural Networks on Neuromorphic Data with Spatiotemporal Fragments [paper]

• Leveraging Sparsity with Spiking Recurrent Neural Networks for Energy-Efficient Keyword Spotting [paper]

ICLR (International Conference on Learning Representations)

• Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes [paper] [code]

• Spiking Convolutional Neural Networks for Text Classification [paper]

• Spikformer: When Spiking Neural Network Meets Transformer [paper] [code]

• Heterogeneous Neuronal and Synaptic Dynamics for Spike-Efficient Unsupervised Learning: Theory and Design Principles [paper]

• A Unified Framework for Soft Threshold Pruning [paper] [code]

IJCNN (International Joint Conference on Neural Networks)

• Brain-Inspired Spiking Neural Network for Online Unsupervised Time Series Prediction [paper]

• Low Precision Quantization-aware Training in Spiking Neural Networks with Differentiable Quantization Function [paper]

PAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence)

• Fast-SNN: Fast Spiking Neural Network by Converting Quantized ANN [paper] [code]

TNNLS (IEEE Transactions on Neural Networks and Learning Systems)

• Attention-Based Deep Spiking Neural Networks for Temporal Credit Assignment Problems [paper]

• Effective Active Learning Method for Spiking Neural Networks [paper]

• Backpropagation-Based Learning Techniques for Deep Spiking Neural Networks: A Survey [paper]

Neural Networks

• SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networks [paper]

2022

CVPR

• Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation [paper] [code]
• Event-based Video Reconstruction via Potential-assisted Spiking Neural Network [paper] [code]
• Brain-inspired Multilayer Perceptron with Spiking Neurons [paper] [code]
• RecDis-SNN: Rectifying Membrane Potential Distribution for Directly Training Spiking Neural Networks [paper]
• Spiking Transformers for Event-Based Single Object Tracking [paper] [code]
• Optical Flow Estimation for Spiking Camera [paper] [code]

ECCV

• Neuromorphic Data Augmentation for Training Spiking Neural Networks [paper] [code]
• Neural Architecture Search for Spiking Neural Networks [paper] [code]
• Real Spike: Learning Real-valued Spikes for Spiking Neural Networks [paper] [code]
• Lottery Ticket Hypothesis for Spiking Neural Networks [paper]
• Reducing Information Loss for Spiking Neural Networks [paper] [code]

NeurIPS

• GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [paper] [code]
• Biologically Inspired Dynamic Thresholds for Spiking Neural Networks [paper]
• Online Training Through Time for Spiking Neural Networks [paper] [code]
• Mesoscopic modeling of hidden spiking neurons [paper] [code]
• Temporal Effective Batch Normalization in Spiking Neural Networks [paper]
• Differentiable hierarchical and surrogate gradient search for spiking neural networks [paper]
• LTMD: Learning Improvement of Spiking Neural Networks with Learnable Thresholding Neurons and Moderate Dropout [paper]
• Theoretically Provable Spiking Neural Networks [paper]
• Natural gradient enables fast sampling in spiking neural networks [paper]
• Biologically plausible solutions for spiking networks with efficient coding [paper]
• Toward Robust Spiking Neural Network Against Adversarial Perturbation [paper]
• SNN-RAT: Robustness-enhanced Spiking Neural Network through Regularized Adversarial Training [paper]
• Emergence of Hierarchical Layers in a Single Sheet of Self-Organizing Spiking Neurons [paper]
• Training Spiking Neural Networks with Event-driven Backpropagation [paper]
• IM-Loss: Information Maximization Loss for Spiking Neural Networks [paper]
• The computational and learning benefits of Daleian neural networks [paper]
• Dance of SNN and ANN: Solving binding problem by combining spike timing and reconstructive attention [paper]
• Learning Optical Flow from Continuous Spike Streams [paper]
• STNDT: Modeling Neural Population Activity with Spatiotemporal Transformers [paper]

AAAI

• Optimized Potential Initialization for Low-latency Spiking Neural Networks [paper]
• PrivateSNN: Privacy-Preserving Spiking Neural Networks [paper]
• Fully Spiking Variational Autoencoder [paper] [code]
• Spiking Neural Networks with Improved Inherent Recurrence Dynamics for Sequential Learning [paper] [code]
• Spatio-Temporal Recurrent Networks for Event-Based Optical Flow Estimation [paper] [code]
• SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks [paper]
• Multi-Sacle Dynamic Coding Improved Spiking Actor Network for Reinforcement Learning [paper]

ICASSP

• Axonal Delay As a Short-Term Memory for Feed Forward Deep Spiking Neural Networks [paper]
• Gradual Surrogate Gradient Learning in Deep Spiking Neural Networks [paper]
• T-NGA: Temporal Network Grafting Algorithm for Learning to Process Spiking Audio Sensor Events [paper]
• Modeling The Detection Capability Of High-Speed Spiking Cameras [paper]
• DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks [paper]
• Optimizing The Consumption Of Spiking Neural Networks With Activity Regularization [paper]
• Rate Coding Or Direct Coding: Which One Is Better For Accurate, Robust, And Energy-Efficient Spiking Neural Networks? [paper]
• Motif-Topology and Reward-Learning Improved Spiking Neural Network for Efficient Multi-Sensory Integration [paper]
• Event-Based Multimodal Spiking Neural Network with Attention Mechanism [paper]
• A Hybrid Learning Framework for Deep Spiking Neural Networks with One-Spike Temporal Coding [paper]
• Supervised Training of Siamese Spiking Neural Networks with Earth Mover's Distance [paper]
• A Time Encoding Approach to Training Spiking Neural Networks [paper]

ICML

• State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks [paper]
• AutoSNN: Towards Energy-Efficient Spiking Neural Networks [paper] [code]
• Scalable Spike-and-Slab [paper] [code]
• Neural Network Poisson Models for Behavioural and Neural Spike Train Data [paper]

IJCAI

• Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes [paper] [code]
• Spiking Graph Convolutional Networks [paper] [code]
• Signed Neuron with Memory: Towards Simple, Accurate and High-Efficient ANN-SNN Conversion [paper] [code]
• Self-Supervised Mutual Learning for Dynamic Scene Reconstruction of Spiking Camera [paper]
• Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks [paper] [code]

ICLR

• Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks [paper] [code]
• Spike-inspired rank coding for fast and accurate recurrent neural networks [paper]
• Sequence Approximation using Feedforward Spiking Neural Network for Spatiotemporal Learning: Theory and Optimization Methods [paper]
• Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting [paper] [code]

IJCNN

• Event-Driven Tactile Learning with Location Spiking Neurons [paper] [code]
• Spiking Approximations of the MaxPooling Operation in Deep SNNs [paper] [code]
• Spikemax: Spike-based Loss Methods for Classification [paper]
• Object Detection with Spiking Neural Networks on Automotive Event Data [paper] [code]

NEURAL COMPUTATION

• Training Deep Convolutional Spiking Neural Networks With Spike Probabilistic Global Pooling [paper]

Neural Networks

• Modeling learnable electrical synapse for high precision spatio-temporal recognition [paper]

IEEE TCYB (IEEE Transactions on Cybernetics)

• Toward Efficient Processing and Learning With Spikes: New Approaches for Multispike Learning [paper]

Starchart