Spiking Neural Networks

Also known as SNN

Overview

Spiking neural networks study computation with neurons that integrate inputs over time and communicate through spikes, making them a natural fit for event-based data such as vision, audio, and sensor streams. Common approaches include training with surrogate gradients and backpropagation through time, local plasticity rules such as spike-timing-dependent plasticity, and converting conventional neural networks into spiking ones; researchers also design new neuron dynamics, temporal codes, and spiking attention or state-space models. Applications range from edge sensing and robotics to language, medical imaging, and scientific computing, with implementations on neuromorphic chips, FPGAs, and conventional hardware. A central tension is whether sparse activity yields real energy and latency savings without sacrificing accuracy: results depend on the task, encoding, time steps, and hardware, so deployment-aware benchmarks remain important.

Latest papers

CardsList

358 papers49 papers in the last four weeks, up 40% on the four weeks before. 0.3% of all new papers.

  1. Latency Coding for Efficient and Low-Latency Deep Spiking Neural Networks

    Mar 24, 2026Yi Lu, Jianhao Ding, Zhaofei YuEfficient Neural Network InferenceSpiking Neural Networks

  2. Event-Driven Neuromorphic Vision Enables Energy-Efficient Visual Place Recognition

    Mar 24, 2026Geoffroy Keime, Nicolas Cuperlier, Benoit R. CottereauVisual Place RecognitionNeuromorphic Computing

  3. SPINONet: Scalable Spiking Physics-informed Neural Operator for Computational Mechanics Applications

    Mar 23, 2026Shailesh Garg, Luis Mandl, Somdatta Goswami +1Physics-Informed Neural OperatorsNeural Operators

  4. Neuronal Self-Adaptation Enhances Capacity and Robustness of Representation in Spiking Neural Networks

    Mar 21, 2026Zhuobin Yang, Yeyao Bao, Liangfu Lv +3Spiking Neural NetworksNeural Network Robustness

  5. Brain-inspired AI for Edge Intelligence: a systematic review

    Mar 19, 2026Yingchao Cheng, Meijia Wang, Zhifeng Hao +1Neuromorphic ComputingSpiking Neural Networks

  6. S3T-Former: A Purely Spike-Driven State-Space Topology Transformer for Skeleton Action Recognition

    Mar 18, 2026Naichuan Zheng, Hailun Xia, Zepeng Sun +2Skeleton-Based Action RecognitionSpiking Transformers

  7. An FPGA-Based SoC Architecture with a RISC-V Controller for Energy-Efficient Temporal-Coding Spiking Neural Networks

    Mar 17, 2026Mohammad Javad Sekonji, Ali Mahani, Maryam Mirsadeghi +1Spiking Neural NetworksFPGA-Based Neural Network Acceleration

  8. Linearized Bregman Iterations for Sparse Spiking Neural Networks

    Mar 17, 2026Daniel Windhager, Bernhard A. Moser, Michael LunglmayrSpiking Neural NetworksSparse Neural Networks

  9. SpikeCLR: Contrastive Self-Supervised Learning for Few-Shot Event-Based Vision using Spiking Neural Networks

    Mar 17, 2026Maxime Vaillant, Axel Carlier, Lai Xing Ng +2Self-Supervised Visual Representation LearningEvent-Based Vision

  10. Determinism in the Undetermined: Deterministic Output in Charge-Conserving Continuous-Time Neuromorphic Systems with Temporal Stochasticity

    Mar 16, 2026Jing Yan, Kang You, Zhezhi He +1Neuromorphic ComputingSpiking Neural Networks

  11. S2Act: Simple Spiking Actor

    Mar 16, 2026Ugur Akcal, Seung Hyun Kim, Mikihisa Yuasa +6Spiking Neural NetworksRobotic RL

  12. CATFormer: When Continual Learning Meets Spiking Transformers With Dynamic Thresholds

    Mar 16, 2026Vaishnavi Nagabhushana, Kartikay Agrawal, Ayon BorthakurClass-Incremental LearningSpiking Neural Networks

  13. SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning

    Mar 16, 2026Ran Tao, Qiugang Zhan, Shantian Yang +3Federated LearningHeterogeneous Federated Learning

  14. Spiking Layer-Adaptive Magnitude-based Pruning

    Mar 16, 2026Junqiao Wang, Zhehang Ye, Yuqi OuyangSpiking Neural NetworksNeural Network Pruning

  15. Wi-Spike: A Low-power WiFi Human Multi-action Recognition Model with Spiking Neural Networks

    Mar 15, 2026Nengbo Zhang, Yao Ying, Lu Wang +3Human Activity RecognitionWi-Fi Sensing

  16. SPARQ: Spiking Early-Exit Neural Networks for Energy-Efficient Edge AI

    Mar 15, 2026Parth Patne, Mahdi Taheri, Ali Mahani +3Spiking Neural NetworksEnergy-Efficient ML

  17. MorphSNN: Adaptive Graph Diffusion and Structural Plasticity for Spiking Neural Networks

    Mar 15, 2026Yongsheng Huang, Peibo Duan, Yujie Wu +7Spiking Neural NetworksDynamic Neural Networks

  18. SRAM-Based Compute-in-Memory Accelerator for Linear-decay Spiking Neural Networks

    Mar 13, 2026Hongyang Shang, Shuai Dong, Yahan Yang +3LIF NeuronsSpiking Neural Networks

  19. Chemical Reaction Networks Learn Better than Spiking Neural Networks

    Mar 12, 2026Sophie Jaffard, Ivo F. SbalzariniClassificationDynamical Systems

  20. SNAP-V: A RISC-V SoC with Configurable Neuromorphic Acceleration for Small-Scale Spiking Neural Networks

    Mar 12, 2026Kanishka Gunawardana, Sanka Peeris, Kavishka Rambukwella +4Neuromorphic ComputingEfficient Neural Network Inference

  21. Stable Spike: Dual Consistency Optimization via Bitwise AND Operations for Spiking Neural Networks

    Mar 12, 2026Yongqi Ding, Kunshan Yang, Linze Li +3Spiking Neural NetworksNeuromorphic Computing

  22. An Event-Driven E-Skin System with Dynamic Binary Scanning and real time SNN Classification

    Mar 11, 2026Gaishan Li, Zhengnan Fu, Anubhab Tripathi +2Robotic Tactile SensingTactile Sensing

  23. Intrinsic Numerical Robustness and Fault Tolerance in a Neuromorphic Algorithm for Scientific Computing

    Mar 10, 2026Bradley H. Theilman, James B. AimoneNeuromorphic ComputingNeural Network Robustness

  24. Efficient and robust control with spikes that constrain free energy

    Mar 10, 2026André Urbano, Pablo Lanillos, Sander KeeminkRobust ControlSpiking Neural Networks

  25. DendroNN: Dendrocentric Neural Networks for Energy-Efficient Classification of Event-Based Data

    Mar 10, 2026Jann Krausse, Zhe Su, Kyrus Mama +4Efficient Neural Network InferenceSpiking Neural Networks

  26. Neural Dynamics Self-Attention for Spiking Transformers

    Mar 9, 2026Dehao Zhang, Fukai Guo, Shuai Wang +6Spiking TransformersSpiking Neural Networks