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

CardsList

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

  1. AI at a Turning Point: From ChatGPT through Neural Networks to Neuromorphic AI

    Oct 29, 2026Volker KempeNeuromorphic ComputingSpiking Neural Networks

  2. Hardware-Aware Model Inversion in Memristive Spiking Neural Networks

    Oct 29, 2026Pablo Sorrentino, Fernando M. Quintana, Erika Covi +1Model Inversion AttacksSpiking Neural Networks

    University of Groningen Groningen, The Netherlands · Technical University of Munich Munich, Germany

  3. GC-LIF: Spiking Group-Equivariant Neural Network With Group-Coupled Membrane Dynamics

    Oct 29, 2026Nhan Trong Luu, Duong Trung Luu, Thang Cong TruongEquivariant Neural NetworksSpiking Neural Networks

    College of ICT, Can Tho University, Can Tho, Vietnam. · Center for Digital Transformation and Communication, Can Tho University, Can Tho, Vietnam. · Department of Computer Science and Engineering, The University of Aizu, Japan.

  4. FPGAFly: A 166.7k-Neuron Fruit-Fly Connectome on One FPGA via Deferred Spike Expansion and Shared-Codeword States

    Oct 28, 2026YE ZiyangSpiking Neural NetworksFPGA-Based Neural Network Acceleration

    Department of Electrical Engineering and Information Systems, Graduate School of Engineering, The University of Tokyo, Tokyo, Japan

  5. Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons

    Oct 27, 2026Aurora Micheli, Claudio Gallicchio, Nergis TomenReservoir ComputingSpiking Neural Networks

    Delft University of Technology · University of Pisa

  6. Learning Without Clocks: Partition-Invariant Neural Network

    Oct 27, 2026Han Wang, Jingyuan Bao, Juntao Wu +2Permutation-Invariant LearningSpiking Neural Networks

    Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei 230031, China · Science Island Branch, Graduate School of University of Science and Technology of China, Hefei 230026, China

  7. Keeping Inference in the Radio: Design and Measurement of a Spiking Accelerator for mmWave ISAC Activity Recognition

    Oct 27, 2026Anthony Sánchez, Rafael Ruiz, José A. Belloch +2Spiking Neural NetworksFPGA-Based Neural Network Acceleration

    IMDEA Networks Institute, Madrid, Spain · Universidad Carlos III de Madrid, Leganés, Spain

  8. Spiking Neuromorphic Control for Periodic Orbits Stabilization in Underactuated Robots: A Greedy Lyapunov-Based Approach

    Oct 27, 2026Maksim Surov, Oleg SumenkovRobotic ControlRobot Trajectory Tracking

    The authors are with Mathematical Robotics Science Division, Sirius University of Science and Technology, Olympiyskiy Av. 1, Sirius, 354340 Russia

  9. Hardware-Matched Spiking Neural Networks for Real-Time Purkinje Cell Spike Classification

    Oct 27, 2026Arooba Farhan, Afsah Syed, Muhammad Fahd Ibrahim Bhatti +4Spiking Neural NetworksEfficient Neural Network Inference

    Electrical Engineering Department, Lahore University of Management Sciences, Pakistan · Department of Neuroscience, Erasmus University Medical Center, Rotterdam, The Netherlands

  10. Spiking Neural Networks Are Harder to Steal: A Benchmark Study of Model Stealing Attacks

    Oct 26, 2026Ayana Moshruba, Maryam ParsaModel Extraction AttacksSpiking Neural Networks

    George Mason University, Fairfax, Virginia, USA

  11. Characterizing Privacy Leakage in Spiking Neural Networks: A Systematic Analysis of Temporal Dynamics, Stochasticity, Neuronal Dynamics and Learning Mechanisms

    Oct 26, 2026Ayana Moshruba, Maryam ParsaSpiking Neural NetworksSpike-Based Signal Encoding

    Electrical and Computer Engineering, George Mason University Fairfax, Virginia, USA

  12. ChroNoC: A Tableless TDM Circuit-Switched NoC With Delay-Aware Deployment for Time-Sensitive Neuromorphic Computing

    Oct 25, 2026Mohammad Rasoul Roshanshah, Mehdi Modarressi, Saeed SafariNeuromorphic ComputingNeural Network Hardware Acceleration

    The authors are with the School of Electrical and Computer Engineering, College of Engineering, University of Tehran, Tehran, Iran.

  13. PAFS: Perturbation-Aware Firing Scaffolds for Robust Event-Based SNNs

    Oct 23, 2026Ning Liu, Jun Sun, Hao Guo +6Spiking Neural NetworksNeural Network Robustness

    The University of Western Australia, Australia · Nanjing University, China · The Chinese University of Hong Kong, Hong Kong SAR, China +2

  14. A Resource-Efficient and Precision-Scalable FPGA Accelerator for Spiking Neural Networks Using Minifloat Arithmetic

    Oct 23, 2026Ali Mehrabi, Philip C. JoseFPGA-Based Neural Network AccelerationSpiking Neural Networks

    School of Engineering, Computing, and Science, Western Sydney University, Sydney, Australia

  15. Spike-Aware Gradient-Based Mixed-Precision Quantization of Spiking Neural Networks for Vision Applications

    Oct 21, 2026Rajshekhar Rakshit, Devgokul B., Rakshitha Kalkura +1Mixed-Precision QuantizationSpiking Neural Networks

    Indian Institute Of Technology Madras, Chennai, India

  16. Bio-Inspired Auditory Processing: Coupling Parallel Resonate-and-Fire Dynamics with Ternary Recurrent Networks for Speech Recognition

    Oct 21, 2026Pavlos Poulos, Katelyn Sadorf, Themos Stafylakis +1Automatic Speech RecognitionSpiking Neural Networks

    Department of Informatics, Athens University of Economics and Business, Greece · Archimedes AI, Athena Research Center, Greece · California Institute of Technology, USA +1

  17. SICAF: Time-Varying Focus Bottleneck for Self-Supervised Event-Based Optical Flow with Spiking Neural Network

    Oct 21, 2026Shuangming Yang, Qing He, Shangqi Guo +1Event-Based Optical FlowSpiking Neural Networks

    Tianjin University, Tianjin, China · Tsinghua University, Beijing, China · Xi’an Jiaotong University, Xi’an, China

  18. Model- and Layer-Level Closed-Loop Forecasting with SSM-Based Spiking Neural Networks

    Oct 20, 2026Erik Stolt, Sanja Karilanova, Ayca OzcelikkaleTime Series ForecastingSpiking Neural Networks

    Department of Electrical Engineering, Uppsala University, Uppsala, Sweden

  19. Robust Representation Learning for Spiking Neural Networks based on Conditional Information Bottleneck

    Oct 20, 2026Yuli Zha, Wang Fan, Yixiao Dai +5Spiking Neural NetworksNeural Network Robustness

    College of Computer Science and Artificial Intelligence, Fudan University, Shanghai, 200433, China · Institute of Big Data, Fudan University, Shanghai, 200433, China

  20. A Spiking Ring-Attractor Architecture for Representation and Control of Revolute Robot Joints

    Oct 19, 2026Aung Htet, Alejandro Rodriguez Jimenez, Ruidong Ma +1Continuous Attractor Neural NetworksRobotic Control

    Sheffield Hallam University, Sheffield, UK

  21. SpikeQ: Spike-Guided Post-Training Quantization for Spiking Neural Networks

    Oct 16, 2026Kai Sun, Peibo Duan, Zhanglu Yan +3Spiking Neural NetworksPost-Training Quantization

    Monash University · National University of Singapore · Northeastern University

  22. Upper bounds on the number of causal pieces in spiking neural networks

    Oct 15, 2026Dominik Dold, Dennis Elbrächter, Philipp PetersenSpiking Neural NetworksNeural Network Expressivity

  23. Beyond the Hamming Cliff: Compact Spatial Encodings Preserving Semantic Distance in Spiking Neural Networks

    Oct 15, 2026Sergio Davies, Muhammad Aitsam, Morgan-Tyler Stone +2Spike-Based Signal EncodingNeural Encoding

    Department of Computing and Mathematics, Manchester Metropolitan University, John Dalton Building, Oxford Road, Manchester, M15 6BH, United Kingdom · Centre of Excellence in Artificial Intelligence and Robotics, Sheffield Hallam University, Howard Street, Sheffield, S1 1WB, United Kingdom · Università degli Studi di Catania, Viale Andrea Doria 6, Catania, 95100, Italy

  24. Towards bio-inspired visual navigation: a neuromorphic navigation paradigm for MAVs

    Oct 15, 2026Junjie Jiang, Ankang Zhou, Zheng FangVisual NavigationUAV Navigation

    Faculty of Robot Science and Engineering, Northeastern University, Shenyang 110819, China. · College of Information Science and Engineering, Northeastern University, Shenyang 110819, China.

  25. The Dormant Spiking Neuron: A State-Driven Mechanism for Efficient Spiking Neural Networks

    Oct 15, 2026Ruichen Ma, Yicai Chen, Pujun Zhou +5Spiking Neural NetworksEnergy-Efficient ML

    University of Electronic Science and Technology of China (UESTC) · Shenzhen Institute for Advanced Study, UESTC

  26. Controlling the latency in temporal coded spiking models for neuromorphic datasets

    Oct 14, 2026Alban Gattepaille, Alexandre MuzySpiking Neural Networks

    I3S · ILLS

  27. Design and Analysis of Temporal Representations in Neural Networks

    Oct 14, 2026Alban Colas-Gattepaille, Alexandre MuzyNeural EncodingSpiking Neural Networks

    I3S · ILLS

  28. A Time-Variant Spiking Neuron from a Unified State-Dynamics Perspective

    Oct 14, 2026Jing Yang, Qianhui Liu, Gang Pan +1Spiking Neural NetworksDynamic Neural Networks

    School of Artificial Intelligence, Shandong University, Jinan, China · College of Computer Science and Technology, Zhejiang University, Hangzhou, China · Department of Computer Science, National University of Singapore, Singapore

  29. Saliency-Guided Replay for Continual Learning in Deep Spiking Neural Networks

    Oct 13, 2026Francesco Panetta, Federico Di Valerio, Michela ProiettiStorage-Efficient Continual LearningReplay-Based Continual Learning

    Sapienza University of Rome, Italy · Goethe University Frankfurt, Germany

  30. An FPGA-Based Spiking Neural Network for Spatiotemporal Pattern Learning and Classification

    Oct 12, 2026Jingang Jin, Yue Ma, Zhenhang Zhang +1Spiking Neural NetworksFPGA-Based Neural Network Acceleration

    Department of Electrical Engineering and Computer Science Syracuse University, Syracuse, New York, USA