Skip to content

🔥🔥🔥A collection of some awesome public SNN(Spiking Neural Network) projects.

Notifications You must be signed in to change notification settings

coderonion/awesome-snn

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

39 Commits
 
 

Repository files navigation

Awesome-SNN

Awesome

🔥🔥🔥 This repository lists some awesome SNN(Spiking Neural Network) projects.

Contents

Review

Datasets

Frameworks

  • SpikingJelly | 惊蜇 : SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch. SpikingJelly 是一个基于 PyTorch,使用脉冲神经网络(Spiking Neural Network, SNN)进行深度学习的框架。spikingjelly.readthedocs.io

  • BrainCog | 智脉 : BrainCog is an open source spiking neural network based brain-inspired cognitive intelligence engine for Brain-inspired Artificial Intelligence and brain simulation. More information on braincog can be found on its homepage http://www.brain-cog.network/. "BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation". (arXiv 2022)

  • NCPs : PyTorch and TensorFlow implementation of NCP, LTC, and CfC wired neural models. "Neural circuit policies enabling auditable autonomy". (Nature Machine Intelligence, 2020)

  • CfC : "Closed-form continuous-time neural networks". (Nature Machine Intelligence, 2022)

  • LTCs : "Liquid Time-constant Networks". (AAAI 2021)

  • C. elegans : "A Transparent Window into Biology: A Primer on Caenorhabditis elegans". (Genetics, 2015)

  • VOneNets : "Simulating a Primary Visual Cortex at the Front of CNNs Improves Robustness to Image Perturbations". (NeurIPS 2020)

  • BindsNET : Simulation of spiking neural networks (SNNs) using PyTorch.

  • Brian2 : Brian is a free, open source simulator for spiking neural networks. "Brian 2, an intuitive and efficient neural simulator". (Elife 2019)

  • Brian2CUDA : A brian2 extension to simulate spiking neural networks on GPUs. "Brian2CUDA: flexible and efficient simulation of spiking neural network models on GPUs". (Frontiers in Neuroinformatics 2022)

  • Spiking-Neural-Network : This is the python implementation of hardware efficient spiking neural network.

  • norse : Deep learning with spiking neural networks (SNNs) in PyTorch.

  • snntorch : Deep and online learning with spiking neural networks in Python. "Training Spiking Neural Networks Using Lessons From Deep Learning". (arXiv 2021)

  • snn_toolbox : Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

  • SpyTorch : "Surrogate gradient learning in spiking neural networks: Bringing the power of gradient-based optimization to spiking neural networks". (IEEE Signal Processing Magazine 2019)

  • slayerPytorch : PyTorch implementation of SLAYER for training Spiking Neural Networks . "Slayer: Spike layer error reassignment in time". (NeurIPS 2018)

  • Spiking-Neural-Network-SNN-with-PyTorch-where-Backpropagation-engenders-STDP : Spiking Neural Network (SNN) with PyTorch : towards bridging the gap between deep learning and the human brain.

  • PySNN : Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration.

  • yjwu17/STBP-for-training-SpikingNN : Spatio-temporal BP for spiking neural networks.

  • thiswinex/STBP-simple : A simple direct training implement for SNNs using Spatio-Temporal Backpropagation.

  • ZLkanyo009/STBP-train-and-compression : STBP is a way to train SNN with datasets by Backward propagation.Using this Repositories allows you to train SNNS with STBP and quantize SNNS with QAT to deploy to neuromorphological chips like Loihi and Tianjic.

  • SPAIC : Spike-based artificial intelligence computing platform. "Darwin-S: A Reference Software Architecture for Brain-Inspired Computers". (IEEE Computer 2022)

  • yhhhli/SNN_Calibration : Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021. "A free lunch from ANN: Towards efficient, accurate spiking neural networks calibration". (ICML 2021). "Converting Artificial Neural Networks to Spiking Neural Networks via Parameter Calibration". (arXiv 2022)

  • gmtiddia/working_memory_spiking_network : Spiking network model and analysis scripts for the preprint "Simulations of Working Memory Spiking Networks driven by Short-Term Plasticity".

  • Brain-Cog-Lab/Conversion_Burst : "Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes". (IJCAI 2022)

  • Brain-Cog-Lab/BP-STA : "Backpropagation with Biologically Plausible Spatio-Temporal Adjustment For Training Deep Spiking Neural Networks". (Cell Patterns 2022)

  • Borzyszkowski/SNN-CMS : Spiking Neural Networks accelerated on the Intel Loihi chips for LHC experiments, at CMS detector. Project of the European Organization for Nuclear Research (CERN) in collaboration with Intel Labs.

  • TJXTT/SNN2ANN : "SNN2ANN: A Fast and Memory-Efficient Training Framework for Spiking Neural Networks". (arXiv 2022)

  • sPyMem : sPyMem: spike-based bio-inspired memory models.

  • romainzimmer/s2net : Supervised Spiking Network.

  • combra-lab/snn-eeg : PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware. "PyTorch and Loihi implementation of the Spiking Neural Network for decoding EEG on Neuromorphic Hardware". (TMLR 2022)

  • SpikingSIM : "SpikingSIM: A Bio-inspired Spiking Simulator". (ISCAS 2022)

  • Mathorga/behema : Spiking neural network implementation inspired by cellular automata for efficiency.

  • synsense/rockpool : A machine learning library for spiking neural networks. Supports training with both torch and jax pipelines, and deployment to neuromorphic hardware.

  • Sinabs : Spiking neural network library based on PyTorch.

  • MungoMeng/Spiking-Inception : A Spiking Inception architecture for unsupervised Spiking Neural Networks (SNNs). "High-parallelism Inception-like Spiking Neural Networks for Unsupervised Feature Learning". (Neurocomputing 2021). "Spiking Inception Module for Multi-layer Unsupervised Spiking Neural Networks". (IJCNN 2020).

  • BioLCNet : "BioLCNet: Reward-modulated Locally Connected Spiking Neural Networks". (arXiv 2021)

  • aggelen/Spayk : An open source environment for spiking neural networks.

  • ANNarchy : "ANNarchy: a code generation approach to neural simulations on parallel hardware". (Frontiers in Neuroinformatics 2015)

  • Real-Spike : "Real Spike: Learning Real-valued Spikes for Spiking Neural Networks". (ECCV 2022)

  • Spike-Element-Wise-ResNet : "Deep residual learning in spiking neural networks". (NeurIPS 2021)

  • cuSNN : Spiking Neural Networks in C++ with strong GPU acceleration through CUDA. "Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception". (TPAMI 2020)

  • nengo/pytorch-spiking : Spiking neuron integration for PyTorch. www.nengo.ai/pytorch-spiking/.

  • zhouyanasd/DL-NC : spiking-neural-networks.

  • ShahriarSS/Spyker : High-performance Spiking Neural Networks Library Written From Scratch with C++ and Python Interfaces.

  • STSC-SNN : "STSC-SNN: Spatio-Temporal Synaptic Connection with temporal convolution and attention for spiking neural networks". (Frontiers in Neuroscience, 2022)

  • michaelmelanson/spiking-neural-net : A spiking neural network simulation library.

  • STSC-SNN : Multi-scale spiking network model of macaque visual cortex. "Multi-scale account of the network structure of macaque visual cortex". (Brain Structure and Function, 2018). "A multi-scale layer-resolved spiking network model of resting-state dynamics in macaque visual cortical areas". (PLOS Computational Biology, 2018).

Applications

Blogs