Awesome Spiking Neural Networks

Collect some spiking neural network papers & codes. (Actively keep updating)

If you own or find some overlooked SNN papers, you can add them to this document by pull request.

News

News 2026

[2026.03.24] Update SNN-related papers in AAAI 2026 (33 papers), ICLR 2026 (30 papers).

News 2025

[2025.11.01] Update SNN-related papers in Nature, Science 2025 (11 papers).

[2025.10.31] Update SNN-related papers in Neurips 2025 (30 papers).

[2025.05.26] Update SNN-related papers in ICML 2025 (18 papers), IJCAI (11 papers), ICCV (7 papers), and ACM MM (9 papers).

[2025.04.11] Update SNN-related papers in ICLR 2025 (11 papers), CVPR 2025 (14 papers).

[2025.02.06] Update SNN-related papers in AAAI 2025 (18 papers).

News 2024

[2024.11.13] Update SNN-related papers in NeurIPS 2024 (18 papers).

[2024.10.31] Update SNN-related papers in ACM MM 2024 (5 papers).

[2024.10.15] Update SNN-related papers in ECCV 2024 (8 papers).

[2024.05.29] Update SNN-related papers in ICML 2024 (13 papers), IJCAI 2024 (5).

[2024.04.29] Update SNN-related papers in ICLR 2024 (17 papers), AAAI 2024 (8), CVPR 2024 (3).

News 2023

[2023.12.31] Update SNN-related papers in TPAMI 2023, Frontiers in Neuroscience 2023.

[2023.10.31] Update SNN-related papers in CVPR 2023 (2 papers), ICML 2023 (2), IJCAI 2023 (3), and ICCV 2023 (10), NeurIPS 2023 (12).

[2023.06.25] Update SNN-related papers in ICLR 2023 (6 papers), AAAI 2023 (6 papers).

Papers

2026

Nature, Science, Cell

AAAI, ICLR

• Robustify Spiking Neural Networks via Dominant Singular Deflation under Heterogeneous Training Vulnerability (ICLR 2026). [paper]
• A Brain-Inspired Gating Mechanism Unlocks Robust Computation in Spiking Neural Networks (ICLR 2026). [paper]
• Training Deep Normalization-Free Spiking Neural Networks with Lateral Inhibition. (ICLR 2026). [paper]
• 3DSMT: A Hybrid Spiking Mamba-Transformer for Point Cloud Analysis. (ICLR 2026). [paper]
• Neural Dynamics Self-Attention for Spiking Transformers. (ICLR 2026). [paper]
• Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks. (ICLR 2026). [paper]
• Cannistraci-Hebb Training on Ultra-Sparse Spiking Neural Networks. (ICLR 2026). [paper]
• CaRe-BN: Precise Moving Statistics for Stabilizing Spiking Neural Networks in Reinforcement Learning. (ICLR 2026). [paper]
• Otters: An Energy-Efficient Spiking Transformer via Optical Time-to-First-Spike Encoding. (ICLR 2026). [paper]
• Online Pseudo-Zeroth-Order Training of Neuromorphic Spiking Neural Networks. (ICLR 2026). [paper]
• SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network. (ICLR 2026). [paper]
• Robust Spiking Neural Networks Against Adversarial Attacks. (ICLR 2026). [paper]
• TP-Spikformer: Token Pruned Spiking Transformer. (ICLR 2026). [paper]
• Breaking Gradient Temporal Collinearity for Robust Spiking Neural Networks. (ICLR 2026). [paper]
• Random Spiking Neural Networks are Stable and Spectrally Simple. (ICLR 2026). [paper]
• Many Eyes, One Mind: Temporal Multi-Perspective and Progressive Distillation for Spiking Neural Networks. (ICLR 2026). [paper]
• Robust Selective Activation with Randomized Temporal K-Winner-Take-All in Spiking Neural Networks for Continual Learning. (ICLR 2026). [paper]
• Towards Lossless Memory-efficient Training of Spiking Neural Networks via Gradient Checkpointing and Spike Compression. (ICLR 2026). [paper]
• Beyond Linear Processing: Dendritic Bilinear Integration in Spiking Neural Networks. (ICLR 2026). [paper]
• Spiking Discrepancy Transformer for Point Cloud Analysis. (ICLR 2026). [paper]
• PredNext: Explicit Cross-View Temporal Prediction for Unsupervised Learning in Spiking Neural Networks. (ICLR 2026). [paper]
• Difference Predictive Coding for Training Spiking Neural Networks. (ICLR 2026). [paper]
• Advancing Spatiotemporal Representations in Spiking Neural Networks via Parametric Invertible Transformation. (ICLR 2026). [paper]
• Fractional-Order Spiking Neural Network. (ICLR 2026). [paper]
• SpikeGen: Decoupled “Rods and Cones” Visual Representation Processing with Latent Generative Framework. (ICLR 2026). [paper]
• Biologically Plausible Learning via Bidirectional Spike-Based Distillation. (ICLR 2026). [paper]
• Distribution-Aware Multi-Granularity Phase Coding: Towards Lower Conversion Error for Spike-Driven Large Language Models. (ICLR 2026). [paper]
• SpikeStereoNet: A Brain-Inspired Framework for Stereo Depth Estimation from Spike Streams. (ICLR 2026). [paper]
• SpikePingpong: Spike Vision-based Fast-Slow Pingpong Robot System. (ICLR 2026). [paper]
• Spike-based Digital Brain: a novel fundamental model for brain activity analysis. (ICLR 2026). [paper]
• Activation-wise Propagation: A One-Timestep Strategy for Spiking Neural Networks (AAAI 2026). [paper]
• SpikingIR: A Novel Converted Spiking Neural Network for Efficient Image Restoration (AAAI 2026). [paper]
• A Closer Look at Knowledge Distillation in Spiking Neural Network Training (AAAI 2026). [paper]
• Optimization Method for Surrogate Function in Spiking Neural Networks Based on Membrane Potential Distribution (AAAI 2026). [paper]
• Parallel Training Time-to-First-Spike Spiking Neural Networks (AAAI 2026). [paper]
• HardF-SNN: Hardware-Friendly Quantization for Spiking Neural Networks with Efficient Integer-Arithmetic-Only Inference (AAAI 2026). [paper]
• SpikCommander: A High-performance Spiking Transformer with Multi-view Learning for Efficient Speech Command Recognition (AAAI 2026). [paper]
• Timestep-Compressed Attack on Spiking Neural Networks Through Timestep-Level Backpropagation (AAAI 2026). [paper]
• Firing Bits Where It Matters: Spiking-Guided Just Recognizable Distortion Modeling for Machine-Centric Video Coding (AAAI 2026). [paper]
• MPD-SGR: Robust Spiking Neural Networks with Membrane Potential Distribution-Driven Surrogate Gradient Regularization (AAAI 2026). [paper]
• Training-Free ANN-to-SNN Conversion for High-Performance Spiking Transformers (AAAI 2026). [paper]
• Spikingformer: A Key Foundation Model for Spiking Neural Networks (AAAI 2026). [paper]
• I2E: Real-Time Image-to-Event Conversion for High-Performance Spiking Neural Networks (AAAI 2026). [paper]
• S³: Spiking Neurons as an Isolating Segmenter for Brain Signal Decoding (AAAI 2026). [paper]
• TDSNNs: Competitive Topographic Deep Spiking Neural Networks for Visual Cortex Modeling (AAAI 2026). [paper]
• Temporal Dynamics Enhancer for Directly Trained Spiking Object Detectors (AAAI 2026). [paper]
• Spiking Heterogeneous Graph Attention Networks (AAAI 2026). [paper]
• Oligodendrocyte-Driven Spiking Neural Model (AAAI 2026). [paper]
• HLML-SNN：Fast Continual Learning in Spiking Neural Networks Achieved via Hebbian Learning-Driven Meta-Learning (AAAI 2026). [paper]
• DS-ATGO: Dual-Stage Synergistic Learning via Forward Adaptive Threshold and Backward Gradient Optimization for Spiking Neural Networks (AAAI 2026). [paper]
• Pseudo-Spiking Neurons: A Noise-Based Training Framework for Heterogeneous-Latency Spiking Neural Networks (AAAI 2026). [paper]
• Spatial-Frequency Spiking Neural Network for Underwater Object Detection (AAAI 2026). [paper]
• SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning (AAAI 2026).[paper]
• Dynamic Weight Adaptation in Spiking Neural Networks Inspired by Biological Homeostasis (AAAI 2026).[paper]
• GT-SNT: A Linear-Time Transformer for Large-Scale Graphs via Spiking Node Tokenization (AAAI 2026). [paper]
• Exploring the Potentials of Spiking Neural Networks for Image Deraining (AAAI 2026). [paper]
• Spiking-Aided Neural Architecture for Efficient and Robust WiFi Sensing (AAAI 2026). [paper]
• Stabilizing Spiking Neurons Through Biologically Inspired Polarization (AAAI 2026). [paper]
• Spike Stream Memory Transfer for Dynamic Scene Reconstruction (AAAI 2026).
• LAS: Loss-less ANN-SNN Conversion for Fully Spike-Driven Large Language Models (AAAI 2026). [paper]
• Spike Imaging Velocimetry: Dense Motion Estimation of Fluids Using Spike Streams (AAAI 2026).
• BulletTime4D: Towards High Spatio-Temporal Resolution Dynamic Scene Rendering via Spike-Guided Stereo Vision (AAAI 2026).
• Robust Noise Modeling for Spike Camera via Time-Interval Quantification and Spike-DSLR Multimodal Dataset in Low-Light Imaging (AAAI 2026).
• HLML-SNN：Fast Continual Learning in Spiking Neural Networks Achieved via Hebbian Learning-Driven Meta-Learning(AAAI 2026). [paper]
• Generalized Threshold Optimization with Harmony Multi-Threshold Neurons for Accurate ANN-to-SNN Conversion (AAAI 2026). [paper]
• HypoxSpike: Ternary Spiking Neural Network for Opioid Overdose Detection (AAAI 2026). [paper]
• Bi-Spectrum Distillation: Addressing Spectral Mismatch in ANN-SNN Knowledge Transfer (AAAI 2026). [paper]
• Towards Training-Free and Accurate ANN-to-SNN Conversion via Activation-Aware Redistribution (AAAI 2026). [paper]

2025

Nature, Science, Cell

• Spiking neural networks with fatigue spike-timing-dependent plasticity learning using hybrid memristor arrays (Nature Electronics, 2026). [paper]
• Neuromorphic computing paradigms enhance robustness through spiking neural networks (Nature Communications, 2025). [paper][code]
• A spiking artificial neuron based on one diffusive memristor, one transistor and one resistor (Nature Electronics, 2025). [paper][code]
• A biologically inspired artificial neuron with intrinsic plasticity based on monolayer molybdenum disulfide (Nature Electronics, 2025). [paper]
• Modeling macroscopic brain dynamics with brain-inspired computing architecture (Nature Communications, 2025). [paper]
• A frugal Spiking Neural Network for unsupervised multivariate temporal pattern classification and multichannel spike sorting (Nature Communications, 2025). [paper][code]
• Efficient and robust temporal processing with neural oscillations modulated spiking neural networks (Nature Communications, 2025). [paper][code]
• Covariant spatio-temporal receptive fields for spiking neural networks (Nature Communications, 2025). [paper][code]
• A multisynaptic spiking neuron for simultaneously encoding spatial and temporal dynamics in spiking neural networks (Nature Communications, 2025). [paper][code]
• Advancing spatio-temporal processing through adaptation in spiking neural networks (Nature Communications, 2025). [paper][code]
• Topology optimization of random memristors for input-aware dynamic SNN (Science Advances, 2025). [paper][code]
• Fully memristive spiking neural network for energy-efficient graph learning (Science Advances, 2025). [paper]

AAAI, ICLR, CVPR, ICML, IJCAI, ICCV, ACM MM, Neurips

• Adaptive Surrogate Gradients for Sequential Reinforcement Learning in Spiking Neural Networks (Neurips 2025). [paper] [code]
• Toward Relative Positional Encoding in Spiking Transformers (Neurips 2025). [paper] [code]
• High Dynamic Range Imaging with Time-Encoding Spike Camera (Neurips 2025). [paper] [code]
• Bipolar Self-attention for Spiking Transformers (Neurips 2025). [paper] [code]
• Spike-timing-dependent Hebbian learning as noisy gradient descent (Neurips 2025). [paper]
• Spike-RetinexFormer: Rethinking Low-light Image Enhancement with Spiking Neural Networks (Neurips 2025). [paper]
• SPACE: SPike-Aware Consistency Enhancement for Test-Time Adaptation in Spiking Neural Networks (Neurips 2025). [paper] [code]
• MI-TRQR: Mutual Information-Based Temporal Redundancy Quantification and Reduction for Energy-Efficient Spiking Neural Networks (Neurips 2025). [paper] [code]
• Spik-NeRF: Spiking Neural Networks for Neural Radiance Fields (Neurips 2025). [paper]
• Dendritic Resonate-and-Fire Neuron for Effective and Efficient Long Sequence Modeling (Neurips 2025). [paper] [code]
• Spiking Neural Networks Need High-Frequency Information (Neurips 2025). [paper] [code]
• Activity Pruning for Efficient Spiking Neural Networks (Neurips 2025). [paper] [code]
• Multiplication-Free Parallelizable Spiking Neurons with Efficient Spatio-Temporal Dynamics (Neurips 2025). [paper] [code]
• SpikingVTG: A Spiking Detection Transformer for Video Temporal Grounding (Neurips 2025). [paper] [code]
• S$^2$M-Former: Spiking Symmetric Mixing Branchformer for Brain Auditory Attention Detection (Neurips 2025). [paper] [code]
• Local-Global Coupling Spiking Graph Transformer for Brain Disorders Diagnosis from Two Perspectives (Neurips 2025). [paper]
• A Scalable, Causal, and Energy Efficient Framework for Neural Decoding with Spiking Neural Networks (Neurips 2025). [paper] [code]
• Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks (Neurips 2025). [paper] [code]
• Adaptive Fission: Post-training Encoding for Low-latency Spike Neural Networks (Neurips 2025). [paper] [code]
• S$^2$NN: Sub-bit Spiking Neural Networks (Neurips 2025). [paper] [code]
• Seemingly Redundant Modules Enhance Robust Odor Learning in Fruit Flies (Neurips 2025). [paper] [code]
• Fully Spiking Neural Networks for Unified Frame-Event Object Tracking (Neurips 2025). [paper] [code]
• Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training (Neurips 2025). [paper] [code]
• Learning the Plasticity: Plasticity-Driven Learning Framework in Spiking Neural Networks (Neurips 2025). [paper]
• HetSyn: Versatile Timescale Integration in Spiking Neural Networks via Heterogeneous Synapses (Neurips 2025). [paper] [code]
• Unveiling the Spatial-temporal Effective Receptive Fields of Spiking Neural Networks (Neurips 2025). [paper] [code]
• Brain-like Variational Inference (Neurips 2025). [paper] [code]
• Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control (Neurips 2025). [paper] [code]
• Synergy Between the Strong and the Weak: Spiking Neural Networks are Inherently Self-Distillers (Neurips 2025). [paper]
• Spike4DGS: Towards High-Speed Dynamic Scene Recontruction with 4D Gaussian Splatting via a Spike Camera Array (Neurips 2025). [paper] [code]
• Toward End-to-End Bearing Fault Diagnosis for Industrial Scenarios with Spiking Neural Networks (KDD 2025). [paper][code]
• DSF-Net: Dynamic Sparse Fusion of Event-RGB via Spike-Triggered Attention for High-Speed Detection (ACM MM 2025).
• ESOD: Event-Based Small Object Detection (ACM MM 2025).
• E-4DGS: High-Fidelity Dynamic Reconstruction from the Multi-view Event Cameras (ACM MM 2025).
• Incorporating the Refractory Period into Spiking Neural Networks through Spike-Triggered Threshold Dynamics (ACM MM 2025).
• Signal-SGN: A Spiking Graph Convolutional Network for Skeleton Action Recognition via Learning Temporal-Frequency Dynamics (ACM MM 2025).
• SGM-Transformer: Rethinking Gradient Information Loss and Compensation in Spiking Neural Networks (ACM MM 2025).
• Advanced SpikingYOLOX: Extending Spiking Neural Network on Object Detection with Spike-based Partial Self-Attention and 2D-Spiking Transformer (ACM MM 2025).
• Spiking Neural Networks with Temporal Attention-Guided Adaptive Fusion for imbalanced Multi-modal Learning (ACM MM 2025).
• Temporal-coded Spiking Transformer (ACM MM 2025).
• ClearSight: Human Vision-Inspired Solutions for Event-Based Motion Deblurring (ICCV 2025). [paper]
• Robust Unfolding Network for HDR Imaging with Modulo Cameras (ICCV 2025). [paper]
• SpikeDiff: Zero-shot High-Quality Video Reconstruction from Chromatic Spike Camera and Sub-millisecond Spike Streams (ICCV 2025). [paper]
• Noise-Modeled Diffusion Models for Low-Light Spike Image Restoration (ICCV 2025). [paper]
• Efficient Spiking Point Mamba for Point Cloud Analysis (ICCV 2025). [paper]
• SpikePack: Enhanced Information Flow in Spiking Neural Networks with High Hardware Compatibility (ICCV 2025). [paper]
• SpiLiFormer: Enhancing Spiking Transformers with Lateral Inhibition (ICCV 2025). [paper]
• Adaptive Gradient Learning for Spiking Neural Networks by Exploiting Membrane Potential Dynamics (IJCAI 2025). [paper]
• ILIF: Temporal Inhibitory Leaky Integrate-and-Fire Neuron for Overactivation in Spiking Neural Networks (IJCAI 2025). [paper]
• Neuromorphic Sequential Arena: A Benchmark for Neuromorphic Temporal Processing (IJCAI 2025). [paper]
• MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion (IJCAI 2025). [paper]
• A Fast and Accurate ANN-SNN Conversion Algorithm with Negative Spikes (IJCAI 2025). [paper]
• ECC-SNN: Cost-Effective Edge-Cloud Collaboration for Spiking Neural Networks (IJCAI 2025). [paper]
• Cost-Effective On-Device Sequential Recommendation with Spiking Neural Networks (IJCAI 2025). [paper]
• SCNNs: Spike-based Coupling Neural Networks for Understanding Structural-Functional Relationships in the Human Brain (IJCAI 2025). [paper]
• Exploiting Label Skewness for Spiking Neural Networks in Federated Learning (IJCAI 2025). [paper]
• Binary Event-Driven Spiking Transformer (IJCAI 2025). [paper]
• Tackling Long-Tailed Data Challenges in Spiking Neural Networks via Heterogeneous Knowledge Distillation (IJCAI 2025). [paper]
• SpikeVideoFormer: An Efficient Spike-Driven Video Transformer with Hamming Attention and $\mathcal{O}(T)$ Complexity (ICML 2025). [paper]
• Efficient ANN-SNN Conversion with Error Compensation Learning (ICML 2025). [paper]
• Differential Coding for Training-Free ANN-to-SNN Conversion (ICML 2025). [paper]
• Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment (ICML 2025). [paper]
• ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks (ICML 2025). [paper]
• TTFSFormer: A TTFS-based Lossless Conversion of Spiking Transformer (ICML 2025). [paper]
• BSO: Binary Spiking Online Optimization (ICML 2025). [paper]
• Delay-DSGN: A Dynamic Spiking Graph Neural Network with Delay Mechanisms for Evolving Graph (ICML 2025). [paper]
• TS-SNN: Temporal Shift Module for Spiking Neural Networks (ICML 2025). [paper]
• SpikF: Spiking Fourier Network for Efficient Long-term Prediction (ICML 2025). [paper]
• Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning (ICML 2025). [paper]
• Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation (ICML 2025). [paper]
• Efficient Parallel Training Methods for Spiking Neural Networks with Constant Time Complexity (ICML 2025). [paper]
• Training High Performance Spiking Neural Networks by Temporal Model Calibration (ICML 2025). [paper]
• Temporal Misalignment in ANN-SNN Conversion and Its Mitigation via Probabilistic Spiking Neurons (ICML 2025). [paper]
• Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time (ICML 2025). [paper]
• Hybrid Spiking Vision Transformer for Object Detection with Event Cameras (ICML 2025). [paper]
• Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model (ICML 2025). [paper]
• EventGPT: Event Stream Understanding with Multimodal Large Language Models (CVPR 2025). [paper] [code]
• Spk2SRImgNet: Super-Resolve Dynamic Scene from Spike Stream via Motion Aligned Collaborative Filtering (CVPR 2025). [paper]
• Decision SpikeFormer: Spike-Driven Transformer for Decision Making (CVPR 2025). [paper]
• Self-Supervised Learning for Color Spike Camera Reconstruction (CVPR 2025). [paper]
• USP-Gaussian: Unifying Spike-based Image Reconstruction, Pose Correction and Gaussian Splatting (CVPR 2025). [paper]
• VISTREAM: Improving Computation Efficiency of Visual Perception Streaming via Law-of-Charge-Conservation Inspired Spiking Neural Network (CVPR 2025). [paper]
• Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacement (CVPR 2025). [paper]
• Spiking Transformer: Introducing Accurate Addition-Only Spiking Self-Attention for Transformer (CVPR 2025). [paper]
• Brain-Inspired Spiking Neural Networks for Energy-Efficient Object Detection (CVPR 2025). [paper]
• Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks (CVPR 2025). [paper]
• STAA-SNN: Spatial-Temporal Attention Aggregator for Spiking Neural Networks (CVPR 2025). [paper]
• Towards Effective and Sparse Adversarial Attack on Spiking Neural Networks via Breaking Invisible Surrogate Gradients (CVPR 2025). [paper]
• Rethinking Spiking Self-Attention Mechanism: Implementing α-XNOR Similarity Calculation in Spiking Transformers (CVPR 2025). [paper]
• Spiking Transformer with Spatial-Temporal Attention (CVPR 2025). [paper]
• Quantized Spike-driven Transformer (ICLR 2025). [paper]
• Rethinking Spiking Neural Networks from an Ensemble Learning Perspective (ICLR 2025). [paper]
• DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks (ICLR 2025). [paper]
• QP-SNN: Quantized and Pruned Spiking Neural Networks (ICLR 2025). [paper]
• Temporal Flexibility in Spiking Neural Networks: Towards Generalization Across Time Steps and Deployment Friendliness (ICLR 2025). [paper]
• P-SpikeSSM: Harnessing Probabilistic Spiking State Space Models for Long-Range Dependency Tasks (ICLR 2025). [paper]
• TS-LIF: A Temporal Segment Spiking Neuron Network for Time Series Forecasting (ICLR 2025). [paper]
• Improving the Sparse Structure Learning of Spiking Neural Networks from the View of Compression Efficiency (ICLR 2025). [paper]
• SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spiking (ICLR 2025). [paper]
• Spiking Vision Transformer with Saccadic Attention (ICLR 2025). [paper]
• SpikeGS: Reconstruct 3D scene captured by a fast moving bio-inspired camera (AAAI 2025). [paper]
• Rethinking High-speed Image Reconstruction Framework with Spike Camera (AAAI 2025). [paper] [code]
• Spiking Point Transformer for Point Cloud Classification (AAAI 2025).
• Efficient 3D Recognition with Event-driven Spike Sparse Convolution (AAAI 2025).[paper] [code]
• GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARL (AAAI 2025).[paper]
• EventZoom: A Progressive Approach to Event-Based Data Augmentation for Enhanced Neuromorphic Vision (AAAI 2025).[paper]
• Leveraging Asynchronous Spiking Neural Networks for Ultra Efficient Event-Based Visual Processing (AAAI 2025).
• CREST: An Efficient Conjointly-trained Spike-driven Framework for Event-based Object Detection Exploiting Spatiotemporal Dynamics (AAAI 2025).[paper] [code]
• UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networks (AAAI 2025).
• SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models (AAAI 2025). [paper][code]
• Advancing Spiking Neural Networks towards Multiscale Spatiotemporal Interaction Learning (AAAI 2025). [paper]
• SpikingYOLOX: Improved YOLOX Object Detection with Fast Fourier Convolution and Spiking Neural Networks(AAAI 2025).
• ALADE-SNN: Adaptive Logit Alignment in Dynamically Expandable Spiking Neural Networks for Class Incremental Learning (AAAI 2025).[paper]
• Efficient Spike-driven Transformer For High-performance Image Segmentation (AAAI 2025).[paper] [code]
• Towards Accurate Binary Spiking Neural Networks: Learning with Adaptive Gradient Modulation Mechanism (AAAI 2025).
• Adaptive Calibration: A Unified Conversion Framework of Spiking Neural Networks (AAAI 2025).
• Towards More Discriminative Feature Learning in SNNs with Temporal-Self-Erasing Supervision (AAAI 2025).
• FSTA-SNN: Frequency-based Spatial-Temporal Attention Module for Spiking Neural Networks (AAAI 2025).[paper] [code]

2024

Review

• Direct Training High-Performance Deep Spiking Neural Networks: A Review of Theories and Methods (Frontiers in Neuroscience 2024). [paper] [arxiv]

NeurIPS, ACM MM, ECCV, AAAI, ICLR, Frontiers in Neuroscience, CVPR, ICML, IJCAI

• SpikedAttention: Training-Free and Fully Spike-Driven Transformer-to-SNN Conversion with Winner-Oriented Spike Shift for Softmax Operation (NeurIPS 2024). [paper]
• Spiking Graph Neural Network on Riemannian Manifolds (NeurIPS 2024). [paper]
• Rethinking the Dynamics of Spiking Neural Networks (NeurIPS 2024). [paper]
• Long-Range Feedback Spiking Network Captures Dynamic and Static Representations of the Visual Cortex under Movie Stimuli (NeurIPS 2024). [paper] [code]
• Take A Shortcut Back: Mitigating the Gradient Vanishing for Training Spiking Neural Networks (NeurIPS 2024). [paper]
• Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation (NeurIPS 2024). [paper] [code]
• Latent Diffusion for Neural Spiking Data (NeurIPS 2024). [paper]
• Autonomous Driving with Spiking Neural Networks (NeurIPS 2024). [paper] [code]
• Exact Gradients for Stochastic Spiking Neural Networks Driven by Rough Signals (NeurIPS 2024). [paper]
• Spatio-Temporal Interactive Learning for Efficient Image Reconstruction of Spiking Cameras (NeurIPS 2024). [paper]
• Slack-Free Spiking Neural Network Formulation for Hypergraph Minimum Vertex Cover (NeurIPS 2024). [paper]
• EnOF: Training Accurate Spiking Neural Networks via Enhancing the Output Feature Representation (NeurIPS 2024). [paper]
• Spiking Token Mixer: A event-driven friendly Former structure for spiking neural networks (NeurIPS 2024). [paper] [code]
• SpGesture: Source-Free Domain-adaptive sEMG-based Gesture Recognition with Jaccard Attentive Spiking Neural Network (NeurIPS 2024). [paper] [code]
• Spiking Transformer with Experts Mixture (NeurIPS 2024). [paper]
• FEEL-SNN: Robust Spiking Neural Networks with Frequency Encoding and Evolutionary Leak Factor (NeurIPS 2024). [paper] [code]
• Spiking Neural Network as Adaptive Event Stream Slicer (NeurIPS 2024). [paper]
• Advancing Spiking Neural Networks for Sequential Modeling with Central Pattern Generators (NeurIPS 2024). [paper] [code]
• QKFormer: Hierarchical Spiking Transformer using Q-K Attention (NeurIPS 2024). [paper] [code]
• Q-SNNs: Quantized Spiking Neural Networks (ACM MM 2024). [paper]
• RSC-SNN: Exploring the Trade-off Between Adversarial Robustness and Accuracy in Spiking Neural Networks via Randomized Smoothing Coding (ACM MM 2024). [paper] [code]
• Reversing Structural Pattern Learning with Biologically Inspired Knowledge Distillation for Spiking Neural Networks (ACM MM 2024). [paper]
• Towards High-performance Spiking Transformers from ANN to SNN Conversion (ACM MM 2024). [paper] [code]
• Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks (ACM MM 2024). [paper] [code]
• Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection (ECCV 2024). [paper] [code]
• Spiking Wavelet Transformer (ECCV 2024). [paper] [code]
• Efficient Training of Spiking Neural Networks with Multi-Parallel Implicit Stream Architecture (ECCV 2024). [paper] [code]
• Asynchronous Bioplausible Neuron for Spiking Neural Networks for Event-Based Vision (ECCV 2024). [paper]
• BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation (ECCV 2024). [paper] [code]
• Exploring Vulnerabilities in Spiking Neural Networks: Direct Adversarial Attacks on Raw Event Data (ECCV 2024). [paper]
• EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networks (ECCV 2024). [paper] [code]
• Spike-Temporal Latent Representation for Energy-Efficient Event-to-Video Reconstruction (ECCV 2024). [paper]
• EC-SNN: Splitting Deep Spiking Neural Networks on Edge Devices (IJCAI 2024). [code]
• One-step Spiking Transformer with a Linear Complexity (IJCAI 2024).
• TIM: An Efficient Temporal Interaction Module for Spiking Transformer (IJCAI 2024). [paper] [code]
• Learning a Spiking Neural Network for Efficient Image Deraining (IJCAI 2024). [code]
• LitE-SNN: Designing Lightweight and Efficient Spiking Neural Network through Spatial-Temporal Compressive Network Search and Joint Optimization (IJCAI 2024). [paper]
• Temporal Spiking Neural Networks with Synaptic Delay for Graph Reasoning (ICML 2024). [paper]
• Towards efficient deep spiking neural networks construction with spiking activity based pruning (ICML 2024). [paper]
• Efficient and Effective Time-Series Forecasting with Spiking Neural Networks (ICML 2024). [paper]
• Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networks (ICML 2024). [paper]
• Robust Stable Spiking Neural Networks (ICML 2024). [paper]
• CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks (ICML 2024). [paper]
• NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks (ICML 2024). [paper]
• High-Performance Temporal Reversible Spiking Neural Networks with $O(L)$ Training Memory and $O(1)$ Inference Cost (ICML 2024). [paper]
• Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration (ICML 2024). [paper]
• SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanisms (ICML 2024). [paper]
• Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network (ICML 2024). [paper]
• Enhancing Adversarial Robustness in SNNs with Sparse Gradients (ICML 2024). [paper]
• SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN (ICML 2024). [paper]
• Are Conventional SNNs Really Efficient? A Perspective from Network Quantization (CVPR 2024). [paper]
• SFOD: Spiking Fusion Object Detector (CVPR 2024). [paper] [code]
• SpikingResformer: Bridging ResNet and Vision Transformer in Spiking Neural Networks (CVPR 2024). [paper] [code]
• SGLFormer: Spiking Global-Local-Fusion Transformer with high performance (Frontiers in Neuroscience 2024).[paper] [code]
• Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework (ICLR 2024). [paper]
• Online Stabilization of Spiking Neural Networks (ICLR 2024). [paper]
• SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition (ICLR 2024). [paper]
• Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers (ICLR 2024). [paper]
• Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN (ICLR 2024). [paper]
• Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings (ICLR 2024). [paper] [code]
• Threaten Spiking Neural Networks through Combining Rate and Temporal Information (ICLR 2024). [paper] [code]
• TAB: Temporal Accumulated Batch Normalization in Spiking Neural Networks (ICLR 2024). [paper]
• Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks (ICLR 2024). [paper]
• Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures (ICLR 2024). [paper]
• Adaptive deep spiking neural network with global-local learning via balanced excitatory and inhibitory mechanism (ICLR 2024). [paper]
• Hebbian Learning based Orthogonal Projection for Continual Learning of Spiking Neural Networks (ICLR 2024). [paper] [code]
• A Progressive Training Framework for Spiking Neural Networks with Learnable Multi-hierarchical Model (ICLR 2024). [paper] [code]
• LMUFormer: Low Complexity Yet Powerful Spiking Model With Legendre Memory Units (ICLR 2024). [paper] [code]
• Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips (ICLR 2024). [paper] [code]
• Can we get the best of both Binary Neural Networks and Spiking Neural Networks for Efficient Computer Vision? (ICLR 2024). [paper] [code]
• A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks (ICLR 2024). [paper] [code]
• Ternary Spike: Learning Ternary Spikes for Spiking Neural Networks (AAAI 2024). [paper] [code]
• Memory-Efficient Reversible Spiking Neural Networks (AAAI 2024). [paper] [code]
• Gated Attention Coding for Training High-performance and Efficient Spiking Neural Networks (AAAI 2024). [paper]
• SpikingBERT: Distilling BERT to Train Spiking Language Models Using Implicit Differentiation (AAAI 2024). [paper] [code]
• TC-LIF: A Two-Compartment Spiking Neuron Model for Long-Term Sequential Modelling (AAAI 2024). [paper] [code]
• Shrinking Your TimeStep: Towards Low-Latency Neuromorphic Object Recognition with Spiking Neural Networks (AAAI 2024). [paper]
• Dynamic Spiking Graph Neural Networks (AAAI 2024). [paper]
• An Efficient Knowledge Transfer Strategy for Spiking Neural Networks from Static to Event Domain (AAAI 2024). [paper] [code]

Arxiv

• Brain-Inspired Spiking Neural Networks for Industrial Fault Diagnosis: A Survey, Challenges, and Opportunities. paper
• Q-SNNs: Quantized Spiking Neural Networks. [paper]
• Scalable MatMul-free Language Modeling. [paper] [code]
• QKFormer: Hierarchical Spiking Transformer using Q-K Attention. [paper] [code]
• Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticket. [paper] [code]
• SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network Systems. [paper]
• Astrocyte-Enabled Advancements in Spiking Neural Networks for Large Language Modeling. [paper]

2023

Review

• Direct Learning-Based Deep Spiking Neural Networks: A Review (Frontiers in Neuroscience 2023). [paper]

AAAI, ICLR, CVPR, ICML, IJCAI, ICCV, NeurIPS, TPAMI, Science Advances

• Time series prediction and anomaly detection with recurrent spiking neural networks (IJCNN 2023). [paper]
• SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence (Science Advances 2023). [paper] [code]
• Spike-driven Transformer [paper] [code]
• Parallel Spiking Neurons with High Efficiency and Long-term Dependencies Learning Ability (NeurIPS 2023). [paper] [code]
• Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes (NeurIPS 2023). [paper]
• SEENN: Towards Temporal Spiking Early Exit Neural Networks (NeurIPS 2023). [paper]
• EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks (NeurIPS 2023). [paper]
• Addressing the speed-accuracy simulation trade-off for adaptive spiking neurons (NeurIPS 2023). [paper]
• Enhancing Adaptive History Reserving by Spiking Convolutional Block Attention Module in Recurrent Neural Networks (NeurIPS 2023). [paper]
• Trial matching: capturing variability with data-constrained spiking neural networks (NeurIPS 2023). [paper]
• Evolving Connectivity for Recurrent Spiking Neural Networks (NeurIPS 2023). [paper]
• SparseProp: Efficient Event-Based Simulation and Training of Sparse Recurrent Spiking Neural Networks (NeurIPS 2023). [paper]
• Spiking PointNet: Spiking Neural Networks for Point Clouds (NeurIPS 2023). [paper] [code]
• Exploring Loss Functions for Time-based Training Strategy in Spiking Neural Networks (NeurIPS 2023). [paper]
• Membrane Potential Batch Normalization for Spiking Neural Networks (ICCV 2023). [paper]
• Unleashing the Potential of Spiking Neural Networks with Dynamic Confidence (ICCV 2023). [paper]
• RMP-Loss: Regularizing Membrane Potential Distribution for Spiking Neural Networks (ICCV 2023). [paper]
• Inherent Redundancy in Spiking Neural Networks (ICCV 2023). [paper]
• Temporal-Coded Spiking Neural Networks with Dynamic Firing Threshold: Learning with Event-Driven Backpropagation (ICCV 2023). [paper]
• Efficient Converted Spiking Neural Network for 3D and 2D Classification (ICCV 2023). [paper]
• Deep Directly-Trained Spiking Neural Networks for Object Detection (ICCV 2023). [paper]
• Towards Memory- and Time-Efficient Backpropagation for Training Spiking Neural Networks (ICCV 2023). [paper]
• SSF: Accelerating Training of Spiking Neural Networks with Stabilized Spiking Flow (ICCV 2023). [paper]
• Masked Spiking Transformer (ICCV 2023). [paper]
• Spatial-Temporal Self-Attention for Asynchronous Spiking Neural Networks (IJCAI 2023). [paper]
• Learnable Surrogate Gradient for Direct Training Spiking Neural Networks (IJCAI 2023). [paper]
• Enhancing Efficient Continual Learning with Dynamic Structure Development of Spiking Neural Networks (IJCAI 2023). [paper]
• Adaptive Smoothing Gradient Learning for Spiking Neural Networks (ICML 2023). [paper]
• Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks (ICML 2023). [paper] [code]
• Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks (CVPR 2023). [paper]
• Constructing Deep Spiking Neural Networks from Artificial Neural Networks with Knowledge Distillation (CVPR 2023). [paper]
• Attention Spiking Neural Networks (TPAMI 2023) .[paper] [code]
• Heterogeneous neuronal and synaptic dynamics for spike-efficient unsupervised learning: Theory and design principles (ICLR 2023).[paper]
• Spiking Convolutional Neural Networks for Text Classification (ICLR 2023) .[paper]
• Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes (ICLR 2023).[paper] [code]
• Spikformer: When Spiking Neural Network Meets Transformer (ICLR 2023) .[paper] [code]
• A Unified Framework of Soft Threshold Pruning (ICLR 2023). [paper] [code]
• Bridging the Gap between ANNs and SNNs by Calibrating Offset Spikes (ICLR 2023). [paper] [code]
• Reducing ANN-SNN Conversion Error through Residual Membrane Potential (AAAI 2023). [paper] [code]
• Deep Spiking Neural Networks with High Representation Similarity Model Visual Pathways of Macaque and Mouse (AAAI 2023). [paper]
• ESL-SNNs: An Evolutionary Structure Learning Strategy for Spiking Neural Networks (AAAI 2023). [paper]
• Exploring Temporal Information Dynamics in Spiking Neural Networks (AAAI 2023). [paper] [code]
• Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks(AAAI 2023). [paper] [code]
• Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition(AAAI 2023). [paper]

Arxiv

• Spikingformer: Spike-driven Residual Learning for Transformer-based Spiking Neural Network [paper] [code]
• Enhancing the Performance of Transformer-based Spiking Neural Networks by Improved Downsampling with Precise Gradient Backpropagation [paper] [code]
• Training Full Spike Neural Networks via Auxiliary Accumulation Pathway [paper]
• MSS-DepthNet: Depth Prediction with Multi-Step Spiking Neural Network [paper]
• SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networks [paper] [code]
• Auto-Spikformer: Spikformer Architecture Search [paper]
• Advancing Spiking Neural Networks Towards Deep Residual Learning [paper]

2022

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 (AAAI 2022). [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 (NeurIPS 2022). [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]
• Training Spiking Neural Networks with Local Tandem Learning (NeurIPS 2022). [paper]
• IM-Loss: Information Maximization Loss for Spiking Neural Networks (NeurIPS 2022). [paper]
• Temporal Effective Batch Normalization in Spiking Neural Networks (NeurIPS 2022). [paper]
• Biologically Inspired Dynamic Thresholds for Spiking Neural Networks (NeurIPS 2022). [paper]
• Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks (ICLR 2022). [paper] [code]
• Multi-Level Firing with Spiking DS-ResNet: Enabling Better and Deeper Directly-Trained Spiking Neural Networks (IJCAI 2022). [paper]

2021

NeurIPS, ICCV, IJCAI, ICML, AAAI

• Deep Residual Learning in Spiking Neural Networks (NeurIPS 2021). [paper] [code]
• Spiking Deep Residual Network[paper]
• Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks (ECCV 2021). [paper] [code]
• Pruning of Deep Spiking Neural Networks through Gradient Rewiring [paper] [code]
• A Free Lunch From ANN: Towards Efficient, Accurate Spiking Neural Networks Calibration (ICML 2021). [paper] [code]
• Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networks [paper] [code]
• Sparse Spiking Gradient Descent (NeurIPS 2021). [paper]
• Training Spiking Neural Networks with Accumulated Spiking Flow (AAAI 2021). [paper]
• Temporal-wise Attention Spiking Neural Networks for Event Streams Classification. (ECCV 2021). [paper]

Reference

If you find this repo useful, please consider citing:

@article{zhou2024direct,
  title={Direct training high-performance deep spiking neural networks: a review of theories and methods},
  author={Zhou, Chenlin and Zhang, Han and Yu, Liutao and Ye, Yumin and Zhou, Zhaokun and Huang, Liwei and Ma, Zhengyu and Fan, Xiaopeng and Zhou, Huihui and Tian, Yonghong},
  journal={Frontiers in Neuroscience},
  volume={18},
  pages={1383844},
  year={2024},
  publisher={Frontiers Media SA}
}