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).
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]