Alternatives and similar repositories for hybrid-snn-conversion:

Users that are interested in hybrid-snn-conversion are comparing it to the libraries listed below

• yjwu17 / STBP-for-training-SpikingNN
  Spatio-temporal BP for SNNs
  ☆224Updated 2 years ago
• thiswinex / STBP-simple
  A simple direct training implement for SNNs using Spatio-Temporal Backpropagation
  ☆85Updated 2 years ago
• byin-cwi / Efficient-spiking-networks
  Accurate and efficient Spiking recurrent networks on ECG,SHD,SSC,SOLI,(p)SMNIST,TIMIT
  ☆81Updated 2 years ago
• NeuroCompLab-psu / SNN-Conversion
  ☆37Updated 3 years ago
• nmi-lab / dcll
  ☆42Updated 5 years ago
• stonezwr / TSSL-BP
  Pytorch implementation of TSSL-BP rule for Deep Spiking Neural Networks.
  ☆69Updated last year
• Jackn0 / snn_optimal_conversion_pipeline
  Optimal Conversion of Conventional Artificial Neural Networks to Spiking Neural Networks
  ☆33Updated 3 years ago
• AliLotfi92 / SNNLSTM
  Implementation of Long Short Term Spiking NN
  ☆39Updated 2 years ago
• tavanaei / Spiking-CNN
  Spiking Convolutional Neural Networks
  ☆67Updated 6 years ago
• aa-samad / conv_snn
  Code for "Convolutional spiking neural networks (SNN) for spatio-temporal feature extraction" paper
  ☆126Updated 4 years ago
• pkuxmq / OTTT-SNN
  [NeurIPS 2022] Online Training Through Time for Spiking Neural Networks
  ☆60Updated last year
• nmi-lab / decolle-public
  ☆45Updated 2 years ago
• hewh16 / SNNs-RNNs
  The code associated with Comparing SNNs and RNNs on neuromorphic vision datasets: Similarities and differences.
  ☆52Updated 3 years ago
• 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 …
  ☆28Updated 3 years ago
• surrogate-gradient-learning / pytorch-lif-autograd
  ☆37Updated 3 years ago
• putshua / SNN_conversion_QCFS
  ☆52Updated last year
• fangwei123456 / Parametric-Leaky-Integrate-and-Fire-Spiking-Neuron
  Incorporating Learnable Membrane Time Constant to Enhance Learning of Spiking Neural Networks
  ☆106Updated 2 years ago
• brain-intelligence-lab / temporal_efficient_training
  Code for temporal efficient training
  ☆60Updated 8 months ago
• zbs881314 / Temporal-Coded-Deep-SNN
  ☆28Updated 4 years ago
• Jackn0 / must-read-papers-on-snn
  Collect important papers about snn
  ☆31Updated 3 years ago
• fangwei123456 / Spike-Element-Wise-ResNet
  Deep Residual Learning in Spiking Neural Networks
  ☆164Updated 2 years ago
• MXHX7199 / SNN-SSTDP
  SSTDP is a efficient spiking neural network training framework, which is contributed by Fangxin Liu and Wenbo Zhao.
  ☆34Updated 3 years ago
• cowolff / Simple-Spiking-Neural-Network-STDP
  A simple from scratch implementation of a Spiking-Neural-Network with STDP in Python which is beeing trained on MNIST.
  ☆39Updated 7 months ago
• djsaunde / lm-snn
  Using spiking neurons and spike-timing-dependent plasticity to classify the MNIST handwritten digits.
  ☆158Updated 5 years ago
• XDUSPONGE / SNN_benchmark
  ☆254Updated 3 years ago
• qymeng94 / DSR
  [CVPR 2022] Training High-Performance Low-Latency Spiking Neural Networks by Differentiation on Spike Representation
  ☆50Updated 2 years ago
• yhhhli / SNN_Calibration
  Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021
  ☆86Updated 11 months ago
• alishdipani / NMNIST-STDP-SpiNNaker
  A Spiking Neural Network model for Digit Recognition using the N-MNIST dataset.
  ☆19Updated 4 years ago
• jeshraghian / snn-tha
  Threshold annealing in binarized spiking neural networks
  ☆16Updated 2 years ago
• sujay-pandit / spiking-neural-networks-mnist-classification
  Pure python implementation of unsupervised MNIST classification using Spiking Neural Networks (using STDP)
  ☆28Updated 3 years ago