Spiking Neural Networks

Also known as SNN

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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

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

  1. Neuromorphic Control of a Flapping-Wing Robot on Resource-Constrained Hardware

    May 19, 2026Rim El Filali, Chenrui Feng, Chao Gao +1Efficient Neural Network InferenceAerial Robotics

    Institute for AI Industry Research (AIR), Tsinghua University, Beijing, PR China · Department of Computer Science and Technology, Tsinghua University, Beijing, PR China · Xinchen Qihang Inc., Beijing, PR China

  2. Reinterpreting Safety Thresholds as Neuron Spiking Thresholds

    May 18, 2026Enrico Del Re, Mohamed Sabry, Cristina Olaverri-MonrealAutonomous Driving Safety EvaluationAutonomous Driving

    Johannes Kepler University Linz, Austria; Department Intelligent Transport Systems

  3. QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting

    May 18, 2026Alberto Marchisio, Aayan Ebrahim, Nouhaila Innan +2Multivariate Time Series ForecastingHybrid Quantum-Classical ML

    eBrain Lab, Division of Engineering, New York University Abu Dhabi, PO Box 129188, Abu Dhabi, UAE · Center for Quantum and Topological Systems, NYUAD Research Institute, New York University Abu Dhabi, UAE

  4. Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks

    May 18, 2026Alessio Caviglia, Filippo Marostica, Alessandro Savino +1On-Device TrainingEnergy-Efficient ML

    Control and Computer Engineering Department, Politecnico di Torino, Turin, Italy

  5. Brain-inspired spike-timing plasticity for reliable label-efficient event-camera vision

    May 17, 2026Mohamad Yazan Sadoun, Sarah Sharif, Yaser Mike BanadEvent-Based VisionSpiking Neural Networks

    School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA

  6. Von Economo neurons enable reliable social skill acquisition in recurrent spiking neural networks: a computational account with clinical predictions

    May 17, 2026Esila KeskinNeural ProcessesRecurrent Neural Networks

    School of Computing and Creative Technologies, University of the West of England, Bristol, UK

  7. Scalable neuromorphic computing from autonomous spiking dynamics in a clockless reconfigurable chip

    May 15, 2026Eric Oliveira Gomes, Damien RontaniEnergy-Efficient MLSpiking Neural Networks

    LMOPS UR4423 Laboratory, CentraleSup´elec and Universit´e de Lorraine, Metz F-57070, France

  8. XOResNet: Exclusive-OR Meta-Residuals Facilitate Deep Spiking Neural Networks Learning

    May 15, 2026Jianfang Wu, Junsong WangResidual LearningSpiking Neural Networks

    School of Artificial Intelligence, Shenzhen Technology University, Shenzhen 518118, China · Faculty of Data Science, City University of Macau, Macau 999078, China

  9. Federated Learning of Spiking Neural Networks under Heterogeneous Temporal Resolutions

    May 14, 2026Sanja Karilanova, Subhrakanti Dey, Ayça ÖzçelikkaleSpiking Neural NetworksFederated Learning

    Department of Electrical Engineering, Uppsala University, Sweden

  10. NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework

    May 14, 2026Alessio Caviglia, Filippo Marostica, Roberta Bardini +2Spiking Neural NetworksLocal Learning

    Politecnico di Torino, Control and Computer Engineering Department, Corso Duca degli Abruzzi 24, Torino, I-10129, , Italy

  11. Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients

    May 14, 2026Feifan Zhou, Xiang Wei, Yang Liu +1Spiking Neural NetworksNeural Network Training Dynamics

    School of Artificial and Intelligence, Tianjin University, Tianjin 300072, China

  12. Gradient-Free Training of Spiking Neural Networks via Low-Rank Evolution Strategies

    May 14, 2026Dhruv Patankar, Sachit Ramesha GowdaGradient-Free OptimizationEvolutionary Optimization

    Shunya Research

  13. Not All Timesteps Matter Equally: Selective Alignment Knowledge Distillation for Spiking Neural Networks

    May 14, 2026Kai Sun, Peibo Duan, Yongsheng Huang +4Selective Knowledge DistillationSpiking Neural Networks

    Faculty of Information Technology, Monash University, Australia · School of Software, Northeastern University, China · Department of Medicine, National University of Singapore, Singapore

  14. FiTS: Interpretable Spiking Neurons via Frequency Selectivity and Temporal Shaping

    May 13, 2026Jongmin Choi, Joon Son ChungNeural Network InterpretabilitySpiking Neural Networks

    Korea Advanced Institute of Science and Technology (KAIST)

  15. SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting

    May 13, 2026John R. Minnick, Jinghui Geng, Kamran Hussain +6Neural ProcessesTime Series Forecasting

    Department of Electrical and Computer Engineering, University of California, Santa Cruz, CA, USA · UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA · Department of Computer Science and Engineering, University of California, Santa Cruz, CA, USA +2

  16. Heterogeneous SoC Integrating an Open-Source Recurrent SNN Accelerator for Neuromorphic Edge Computing on FPGA

    May 12, 2026Michelangelo Barocci, Vittorio Fra, Enrico Macii +1Edge ComputingHeterogeneous Computing

    Department of Computer and Control Engineering, Politecnico di Torino, Turin, Italy · Interuniversity Department of Regional and Urban Studies and Planning, Politecnico di Torino, Turin, Italy

  17. STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation

    May 12, 2026Shuhan Ye, Yi Yu, Qixin Zhang +5Synthetic Data GenerationSpiking Neural Networks

    Nanyang Technological University · Jilin University · Wuhan University +1

  18. Multi-Timescale Conductance Spiking Networks: A Sparse, Gradient-Trainable Framework with Rich Firing Dynamics for Enhanced Temporal Processing

    May 12, 2026Alex Fulleda-Garcia, Saray Soldado-Magraner, Josep Maria Margarit-TauléSpiking Neural NetworksNeuromorphic Computing

    Instituto de Microelectrónica de Barcelona (IMB-CNM), Consejo Superior de Investigaciones Científicas (CSIC) Cerdanyola del Vallès, Spain · Department of Neurobiology, University of California Los Angeles (UCLA) Los Angeles, USA · Joint Senior authors

  19. Breaking Global Self-Attention Bottlenecks in Transformer-based Spiking Neural Networks with Local Structure-Aware Self-Attention

    May 12, 2026Lingdong Li, Hangming Zhang, Qiang YuSpiking TransformersEfficient ViTs

    School of Future Technology, Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin University, Tianjin 300354, China · School of Artificial Intelligence, Tianjin Key Laboratory of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin 300354, China

  20. Leveraging Non-Equilibrium ECRAM Dynamics for Short-Term Plasticity in Neuromorphic Circuits

    May 11, 2026Alex Currie, Sean Borkholder, Nithil Harris Manimaran +4LIF NeuronsSpiking Neural Networks

    RAMLab, Department of Electrical and Microelectronic Engineering, Rochester Institute of Technology, Rochester NY, USA · Iontronic and Nanoelectronics Lab, School of Physics and Astronomy, Rochester Institute of Technology, Rochester NY, USA · Brain Lab, Department of Computer Engineering, Rochester Institute of Technology, Rochester NY, USA

  21. Energy-Efficient Implementation of Spiking Recurrent Cells on FPGA

    May 11, 2026Pascal Harmeling, Florent De Geeter, Guillaume DrionEfficient Neural Network InferenceSpiking Neural Networks

  22. Neuromorphic Satellite Intelligence: A Formal Framework for Event-Driven Architectures, Spike-Based Algorithms, and Quantitative Energy-Accuracy Trade-offs

    May 11, 2026Suresh Kumar TP, Vikas AgnihotriNeuromorphic ComputingSpiking Neural Networks

    Department of Electrical and Electronics Engineering, Mangalayatan University, India · Independent Researcher, India

  23. Frequency Matching in Spiking Neural Networks for mmWave Sensing

    May 11, 2026Di Yu, Zhenyu Liao, Changze Lv +7Energy-Efficient MLFrequency-Domain Feature Learning

    College of Computer Science and Technology, Zhejiang University, Hangzhou, China · School of Computer Science, Fudan University, Shanghai, China · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China +1

  24. Encoding and Decoding Temporal Signals with Spiking Bandpass Wavelets

    May 10, 2026Jens Egholm Pedersen, Tony Lindeberg, Peter GerstoftSpike-Based Signal EncodingWavelet Methods

    Department of Electrical and Photonics Engineering Technical University of Denmark Denmark · Department of Computational Science and Technology KTH Royal Institute of Technology Sweden

  25. Uncertainty-Aware Token Importance Estimation in Spiking Transformers

    May 10, 2026Wenxuan Liu, Zecheng Hao, Tong Bu +2Spiking TransformersUncertainty Quantification

    School of Computer Science, Peking University · School of Computer Science, Peking University. · Institute for Artificial Intelligence, Peking University +2

  26. UIESNN: A Scale-Aware Spiking Network for Underwater Image Enhancement

    May 8, 2026Shuang Chen, Ruochen Li, Zihan Zhu +3Underwater Image EnhancementSpiking Neural Networks

    Computer Science Department, Durham University, UK · University of Cambridge · Institute of Biology, University of Graz, Graz, Austria.

  27. Convex Optimization of Spiking Neural Networks with Global and Approximation Guarantees

    May 8, 2026Himanshu Udupi, Calvin Ang, Sungyoon Kim +2Neural Network OptimizationRecurrent Neural Networks

    University of Illinois Urbana-Champaign

  28. Direct-to-Event Spiking Neural Network Transfer

    May 8, 2026Nhan Trong Luu, Duong Trung Luu, Pham Ngoc Nam +1Efficient Neural Network InferenceSpiking Neural Networks

    College of ICT, Can Tho University, Vietnam · CECS, VinUniversity, Hanoi, Vietnam · Center of Digital Transformation and Communication, Can Tho University, Vietnam +1

  29. SAFformer:Improving Spiking Transformer via Active Predictive Filtering

    May 8, 2026Zequan Xie, Weiming Zeng, Yunhua Chen +3Spiking TransformersEfficient ViTs

    School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China · Faculty of Science, Hong Kong Baptist University, China · School of Electronic Information, Wuhan University, China

  30. Benchmarking Fairness in Spiking Neural Networks: Data Bias, Spurious Features, and Hardware Effects

    May 8, 2026Hudi He, Fukun Wang, Zhe Wang +7Benchmark DesignAlgorithmic Fairness

    Jilin University · Nanyang Technological University · RMIT University