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Spiking Deep Networks with LIF Neurons

arXiv 1510.08829 ↗First posted 29 Oct 2015cs.LG cs.NEcited by 63

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Abstract (arXiv)

We train spiking deep networks using leaky integrate-and-fire (LIF) neurons, and achieve state-of-the-art results for spiking networks on the CIFAR-10 and MNIST datasets. This demonstrates that biologically-plausible spiking LIF neurons can be integrated into deep networks can perform as well as other spiking models (e.g. integrate-and-fire). We achieved this result by softening the LIF response function, such that its derivative remains bounded, and by training the network with noise to provide robustness against the variability introduced by spikes. Our method is general and could be applied to other neuron types, including those used on modern neuromorphic hardware. Our work brings more biological realism into modern image classification models, with the hope that these models can inform how the brain performs this difficult task. It also provides new methods for training deep networks to run on neuromorphic hardware, with the aim of fast, power-efficient image classification for robotics applications.

Key facts. Cited by 63 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Oct 2015.

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Citing papers per year: 2021: 8; 2022: 11; 2023: 18; 2024: 15; 2025: 6; 2026: 5.

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  1. 2022Spikformer: When Spiking Neural Network Meets Transformercited by 271
  2. 2021Training Spiking Neural Networks Using Lessons From Deep Learningcited by 259
  3. 2023SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligencecited by 169
  4. 2022Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representationcited by 89
  5. 2021Optimal ANN-SNN Conversion for Fast and Accurate Inference in Deep Spiking Neural Networkscited by 78
  6. 2022Online Training Through Time for Spiking Neural Networkscited by 49
  7. 2024QKFormer: Hierarchical Spiking Transformer using Q-K Attentioncited by 49
  8. 2021Sparse Spiking Gradient Descentcited by 41
  9. 2021Training Feedback Spiking Neural Networks by Implicit Differentiation on the Equilibrium Statecited by 40
  10. 2024Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN Ticketcited by 30
  11. 2023Training Full Spike Neural Networks via Auxiliary Accumulation Pathwaycited by 26
  12. 2021Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networkscited by 23
38 more
  1. 2021Spatio-Temporal Pruning and Quantization for Low-latency Spiking Neural Networkscited by 21
  2. 2023Chasing Day and Night: Towards Robust and Efficient All-Day Object Detection Guided by an Event Cameracited by 21
  3. 2023Spiking Denoising Diffusion Probabilistic Modelscited by 19
  4. 2022Spiking Neural Networks for Frame-based and Event-based Single Object Localizationcited by 18
  5. 2023Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Datacited by 18
  6. 2021One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latencycited by 17
  7. 2024Spiking Convolutional Neural Networks for Text Classificationcited by 10
  8. 2024SpikMamba: When SNN meets Mamba in Event-based Human Action Recognitioncited by 10
  9. 2023SPIDE: A Purely Spike-based Method for Training Feedback Spiking Neural Networkscited by 8
  10. 2024Spiking Neural Network as Adaptive Event Stream Slicercited by 8
  11. 2022Simple and complex spiking neurons: perspectives and analysis in a simple STDP scenariocited by 6
  12. 2023KLIF: An optimized spiking neuron unit for tuning surrogate gradient slope and membrane potentialcited by 6
  13. 2025Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacementcited by 6
  14. 2023Hybrid Spiking Neural Network Fine-tuning for Hippocampus Segmentationcited by 5
  15. 2021Spiking Hyperdimensional Network: Neuromorphic Models Integrated with Memory-Inspired Frameworkcited by 4
  16. 2022Navigating Local Minima in Quantized Spiking Neural Networkscited by 4
  17. 2023SpikeCLIP: A Contrastive Language-Image Pretrained Spiking Neural Networkcited by 4
  18. 2023Addressing the speed-accuracy simulation trade-off for adaptive spiking neuronscited by 4
  19. 2022Intelligence Processing Units Accelerate Neuromorphic Learningcited by 3
  20. 2023Attention-free Spikformer: Mixing Spike Sequences with Simple Linear Transformscited by 3
  21. 2024SVFormer: A Direct Training Spiking Transformer for Efficient Video Action Recognitioncited by 3
  22. 2024Spiking Diffusion Modelscited by 3
  23. 2024Membership Privacy Evaluation in Deep Spiking Neural Networkscited by 3
  24. 2024Hybrid variable spiking graph neural networks for energy-efficient scientific machine learningcited by 3
  25. 2022A noise based novel strategy for faster SNN trainingcited by 2
  26. 2024SQUAT: Stateful Quantization-Aware Training in Recurrent Spiking Neural Networkscited by 2
  27. 2025EventTracer: Fast Path Tracing-based Event Stream Renderingcited by 2
  28. 2022SpikiLi: A Spiking Simulation of LiDAR based Real-time Object Detection for Autonomous Drivingcited by 1
  29. 2022EDeNN: Event Decay Neural Networks for low latency visioncited by 1
  30. 2023Joint ANN-SNN Co-training for Object Localization and Image Segmentationcited by 1
  31. 2023Spike-based computation using classical recurrent neural networkscited by 1
  32. 2023Bitformer: An efficient Transformer with bitwise operation-based attention for Big Data Analytics at low-cost low-precision devicescited by 1
  33. 2023Dynamic Spiking Framework for Graph Neural Networkscited by 1
  34. 2024Learning Monocular Depth from Focus with Event Focal Stackcited by 1
  35. 2025ES-Parkour: Advanced Robot Parkour with Bio-inspired Event Camera and Spiking Neural Networkcited by 1
  36. 2025Dynamic Graph Condensationcited by 1
  37. 2022A temporally and spatially local spike-based backpropagation algorithm to enable training in hardwarecited by 0
  38. 2023Frameworks for SNNs: a Review of Data Science-oriented Software and an Expansion of SpykeTorchcited by 0

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