Awesome-Spiking-Neural-Networks

Collect some spiking neural network papers.

If you own or find some overlooked papers, you can add it to this document by pull request (recommended).

Papers

TPAMI, ICLR, AAAI, ICLR

Attention Spiking Neural Networks [paper] [code]
SPIKFORMER: WHEN SPIKING NEURAL NETWORK MEETS TRANSFORMER [paper] [code]
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes [paper] [code]
A Unified Framework of Soft Threshold Pruning [paper]
Reducing ANN-SNN Conversion Error through Residual Membrane Potential [paper] [code]
Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse [paper]
Reducing ANN-SNN Conversion Error through Residual Membrane Potential [paper] [paper]
Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes [paper] [code]
A Unified Framework of Soft Threshold Pruning [paper]

Arxiv

Enhancing the Performance of Transformer-based Spiking Neural Networks by Improved Downsampling with Precise Gradient Backpropagation [paper] [code]
Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network [paper] [code]
Training Full Spike Neural Networks via Auxiliary Accumulation Pathway [paper]
MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network [paper]
Parallel Spiking Neurons with High Efficiency and Long-term Dependencies Learning Ability [paper] [code]
SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks [paper] [code]

NeurIPS, CVPR, ICLR, AAAI, ICML, Nature Communications

Event-based Video Reconstruction via Potential-assisted Spiking Neural Network [paper] [code]
Optimal ANN-SNN Conversion for High-accuracy and Ultra-low-latency Spiking Neural Networks [paper] [code]
Optimized Potential Initialization for Low-latency Spiking Neural Networks [paper]
AutoSNN: Towards Energy-Efficient Spiking Neural Networks [paper]
Neural Architecture Search for Spiking Neural Networks [paper] [code]
Neuromorphic Data Augmentation for Training Spiking Neural Networks [paper] [code]
State Transition of Dendritic Spines Improves Learning of Sparse Spiking Neural Networks [paper] [code]
Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation [paper] [code]
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks [paper] [code]
Spiking Graph Convolutional Networks [paper] [code]
A calibratable sensory neuron based on epitaxial VO2 for spike-based neuromorphic multisensory system [paper] [code]
Online Training Through Time for Spiking Neural Networks [paper] [code]
Training Spiking Neural Networks with Event-driven Backpropagation [paper] [code]
GLIF: A Unified Gated Leaky Integrate-and-Fire Neuron for Spiking Neural Networks [paper] [code]
Temporal Effective Batch Normalization in Spiking Neural Networks [paper]

NeurIPS, ICCV, IJCAI

Deep Residual Learning in Spiking Neural Networks [paper] [code]
Spiking Deep Residual Network[paper]
Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks [paper] [code]
Pruning of Deep Spiking Neural Networks through Gradient Rewiring [paper] [code]
Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks [paper] [code]