mlsanityData to 7 Oct 2026

SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence

arXiv 2310.16620 ↗First posted 25 Oct 2023cs.NE cs.LG cs.SEcited by 163

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Abstract (arXiv)

Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic chips with high energy efficiency by introducing neural dynamics and spike properties. As the emerging spiking deep learning paradigm attracts increasing interest, traditional programming frameworks cannot meet the demands of the automatic differentiation, parallel computation acceleration, and high integration of processing neuromorphic datasets and deployment. In this work, we present the SpikingJelly framework to address the aforementioned dilemma. We contribute a full-stack toolkit for pre-processing neuromorphic datasets, building deep SNNs, optimizing their parameters, and deploying SNNs on neuromorphic chips. Compared to existing methods, the training of deep SNNs can be accelerated 11×, and the superior extensibility and flexibility of SpikingJelly enable users to accelerate custom models at low costs through multilevel inheritance and semiautomatic code generation. SpikingJelly paves the way for synthesizing truly energy-efficient SNN-based machine intelligence systems, which will enrich the ecology of neuromorphic computing.

Key facts. Cited by 163 papers in the map (data through 7 Oct 2026). Builds on 73 of its 152 references that are in the map. First posted on arXiv 25 Oct 2023.

Builds on

73 of 152 references.

References · 73

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  12. 2017Spatio-Temporal Backpropagation for Training High-performance Spiking Neural Networkscited by 399
38 more
  1. 2021ResNet strikes back: An improved training procedure in timmcited by 365
  2. 2021Deep Residual Learning in Spiking Neural Networkscited by 326
  3. 2015Converting Static Image Datasets to Spiking Neuromorphic Datasets Using Saccadescited by 308
  4. 2020Going Deeper With Directly-Trained Larger Spiking Neural Networkscited by 268
  5. 2018Deep Learning in Spiking Neural Networkscited by 258
  6. 2021Training Spiking Neural Networks Using Lessons From Deep Learningcited by 251
  7. 2018Going Deeper in Spiking Neural Networks: VGG and Residual Architecturescited by 236
  8. 2018Direct Training for Spiking Neural Networks: Faster, Larger, Bettercited by 222
  9. 2016Training Deep Spiking Neural Networks using Backpropagationcited by 203
  10. 2018Long short-term memory and learning-to-learn in networks of spiking neuronscited by 179
  11. 2019Spiking-YOLO: Spiking Neural Network for Energy-Efficient Object Detectioncited by 174
  12. 2019The Heidelberg spiking datasets for the systematic evaluation of spiking neural networkscited by 135
  13. 2021Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networkscited by 134
  14. 2019Enabling Spike-based Backpropagation for Training Deep Neural Network Architecturescited by 119
  15. 2021Accurate and efficient time-domain classification with adaptive spiking recurrent neural networkscited by 113
  16. 2022Attention Spiking Neural Networkscited by 103
  17. 2023SpikeGPT: Generative Pre-trained Language Model with Spiking Neural Networkscited by 82
  18. 2022Object Detection with Spiking Neural Networks on Automotive Event Datacited by 79
  19. 2021Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networkscited by 74
  20. 2015Spiking Deep Networks with LIF Neuronscited by 63
  21. 2022Neural Architecture Search for Spiking Neural Networkscited by 52
  22. 2022Neuromorphic Data Augmentation for Training Spiking Neural Networkscited by 52
  23. 2022HARDVS: Revisiting Human Activity Recognition with Dynamic Vision Sensorscited by 46
  24. 2018BindsNET: A machine learning-oriented spiking neural networks library in Pythoncited by 42
  25. 2022AutoSNN: Towards Energy-Efficient Spiking Neural Networkscited by 40
  26. 2022Optimized Potential Initialization for Low-latency Spiking Neural Networkscited by 39
  27. 2023Reducing ANN-SNN Conversion Error through Residual Membrane Potentialcited by 39
  28. 2022An Analytical Estimation of Spiking Neural Networks Energy Efficiencycited by 38
  29. 2022TCJA-SNN: Temporal-Channel Joint Attention for Spiking Neural Networkscited by 33
  30. 2023Optical flow estimation from event-based cameras and spiking neural networkscited by 33
  31. 2021A Long Short-Term Memory for AI Applications in Spike-based Neuromorphic Hardwarecited by 32
  32. 2020Brain-inspired global-local learning incorporated with neuromorphic computingcited by 28
  33. 2021A Spiking Neural Network for Image Segmentationcited by 27
  34. 2023Training Full Spike Neural Networks via Auxiliary Accumulation Pathwaycited by 26
  35. 2016STDP-based spiking deep convolutional neural networks for object recognitioncited by 24
  36. 2021ES-ImageNet: A Million Event-Stream Classification Dataset for Spiking Neural Networkscited by 24
  37. 2019SpykeTorch: Efficient Simulation of Convolutional Spiking Neural Networks with at most one Spike per Neuroncited by 23
  38. 2021Human-Level Control through Directly-Trained Deep Spiking Q-Networkscited by 23

50 most cited of 73 All 73 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 56; 2025: 64; 2026: 40.

163 papers.

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  1. 2024Scaling Spike-driven Transformer with Efficient Spike Firing Approximation Trainingcited by 57
  2. 2024QKFormer: Hierarchical Spiking Transformer using Q-K Attentioncited by 46
  3. 2024SpikeLM: Towards General Spike-Driven Language Modeling via Elastic Bi-Spiking Mechanismscited by 31
  4. 2024SpikeLLM: Scaling up Spiking Neural Network to Large Language Models via Saliency-based Spikingcited by 29
  5. 2024Spiking-PhysFormer: Camera-Based Remote Photoplethysmography with Parallel Spike-driven Transformercited by 19
  6. 2024Spiker+: a framework for the generation of efficient Spiking Neural Networks FPGA accelerators for inference at the edgecited by 18
  7. 2025UCF-Crime-DVS: A Novel Event-Based Dataset for Video Anomaly Detection with Spiking Neural Networkscited by 18
  8. 2024EAS-SNN: End-to-End Adaptive Sampling and Representation for Event-based Detection with Recurrent Spiking Neural Networkscited by 16
  9. 2024Learning A Spiking Neural Network for Efficient Image Derainingcited by 16
  10. 2024SpikeNAS: A Fast Memory-Aware Neural Architecture Search Framework for Spiking Neural Network-based Embedded AI Systemscited by 12
  11. 2024Autonomous Driving with Spiking Neural Networkscited by 12
  12. 2024LED: A Large-scale Real-world Paired Dataset for Event Camera Denoisingcited by 12
38 more
  1. 2025Rethinking Spiking Neural Networks from an Ensemble Learning Perspectivecited by 12
  2. 2025Towards Effective and Sparse Adversarial Attack on Spiking Neural Networks via Breaking Invisible Surrogate Gradientscited by 9
  3. 2024Autaptic Synaptic Circuit Enhances Spatio-temporal Predictive Learning of Spiking Neural Networkscited by 8
  4. 2024Brain-Inspired Online Adaptation for Remote Sensing with Spiking Neural Networkcited by 8
  5. 2024Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networkscited by 8
  6. 2024Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagationcited by 8
  7. 2025QSViT: A Methodology for Quantizing Spiking Vision Transformerscited by 8
  8. 2024LoAS: Fully Temporal-Parallel Dataflow for Dual-Sparse Spiking Neural Networkscited by 7
  9. 2024Continual Learning with Neuromorphic Computing: Foundations, Methods, and Emerging Applicationscited by 7
  10. 2025Spiking Point Transformer for Point Cloud Classificationcited by 7
  11. 2025SU-YOLO: Spiking Neural Network for Efficient Underwater Object Detectioncited by 7
  12. 2024Epilepsy Seizure Detection and Prediction using an Approximate Spiking Convolutional Transformercited by 6
  13. 2024Efficient Event-Based Object Detection: A Hybrid Neural Network with Spatial and Temporal Attentioncited by 5
  14. 2024FTBC: Forward Temporal Bias Correction for Optimizing ANN-SNN Conversioncited by 5
  15. 2024MK-SGN: A Spiking Graph Convolutional Network with Multimodal Fusion and Knowledge Distillation for Skeleton-based Action Recognitioncited by 5
  16. 2024Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Networkcited by 5
  17. 2024Are Neuromorphic Architectures Inherently Privacy-preserving? An Exploratory Studycited by 5
  18. 2025Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networkscited by 5
  19. 2025Spiking Variational Graph Representation Inference for Video Summarizationcited by 5
  20. 2023Addressing the speed-accuracy simulation trade-off for adaptive spiking neuronscited by 4
  21. 2024SDiT: Spiking Diffusion Model with Transformercited by 4
  22. 2024Deep Event-based Object Detection in Autonomous Driving: A Surveycited by 4
  23. 2025Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Timecited by 4
  24. 2024GRSN: Gated Recurrent Spiking Neurons for POMDPs and MARLcited by 3
  25. 2024SVFormer: A Direct Training Spiking Transformer for Efficient Video Action Recognitioncited by 3
  26. 2024SpikeVoice: High-Quality Text-to-Speech Via Efficient Spiking Neural Networkcited by 3
  27. 2024SNNAX -- Spiking Neural Networks in JAXcited by 3
  28. 2024Membership Privacy Evaluation in Deep Spiking Neural Networkscited by 3
  29. 2024Improvement of Spiking Neural Network with Bit Planes and Color Modelscited by 3
  30. 2024Enhancing SNN-based Spatio-Temporal Learning: A Benchmark Dataset and Cross-Modality Attention Modelcited by 3
  31. 2024Flashy Backdoor: Real-world Environment Backdoor Attack on SNNs with DVS Camerascited by 3
  32. 2025Spiking monocular event based 6D pose estimation for space applicationcited by 3
  33. 2025Event2Vec: Processing Neuromorphic Events Directly by Representations in Vector Spacecited by 3
  34. 2025DVS-PedX: Synthetic-and-Real Event-Based Pedestrian Datasetcited by 3
  35. 2025I2E: Real-Time Image-to-Event Conversion for High-Performance Spiking Neural Networkscited by 3
  36. 2023Fast gradient-free activation maximization for neurons in spiking neural networkscited by 2
  37. 2024Spyx: A Library for Just-In-Time Compiled Optimization of Spiking Neural Networkscited by 2
  38. 2024Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devicescited by 2

50 most cited of 163 All 163 (JSON)