Alternatives and similar repositories for HDC-VSA_cookbook_tutorial

Users that are interested in HDC-VSA_cookbook_tutorial are comparing it to the libraries listed below

• NeuromorphicComputing / SoftHebb
  ☆91Updated last year
• NeuromorphicComputing / STPN
  ☆30Updated 2 years ago
• ncos / pyhdc
  A Python library to support long binary vectors
  ☆20Updated 5 years ago
• nmi-lab / decolle-public
  ☆46Updated 3 years ago
• EPFL-LCN / pub-illing2021-neurips
  Public code for Illing, Ventura, Bellec & Gerstner 2021: Local plasticity rules can learn deep representations using self-supervised cont…
  ☆25Updated last year
• jordan-g / Burstprop
  Code to train on MNIST, CIFAR-10 and ImageNet using burstprop.
  ☆38Updated 4 years ago
• apayeur / spikingburstprop
  Auryn-based simulation of multiplexing and burst-dependent plasticity
  ☆24Updated 4 years ago
• nmi-lab / neural_sampling_machines
  ☆11Updated 2 years ago
• lolemacs / pytorch-eventprop
  A PyTorch implementation of EventProp [https://arxiv.org/abs/2009.08378], a method to train Spiking Neural Networks
  ☆52Updated 5 years ago
• ThomasMiconi / HebbianCNNPyTorch
  Automatic Hebbian learning in multi-layer convolutional networks with PyTorch, by expressing Hebbian plasticity rules as gradients
  ☆40Updated 2 years ago
• meulemansalex / theoretical_framework_for_target_propagation
  Python implementation of the methods in Meulemans et al. 2020 - A Theoretical Framework For Target Propagation
  ☆32Updated last year
• IGITUGraz / eligibility_propagation
  ☆96Updated last year
• open-neuromorphic / hands-on-session-snntorch-230302
  ☆20Updated 2 years ago
• SRKH / S4NN
  Temporal backpropagation for spiking neural networks with one spike per neuron, by S. R. Kheradpisheh and T. Masquelier, International Jo…
  ☆62Updated 4 years ago
• npvoid / SparseSpikingBackprop
  ☆19Updated 3 years ago
• chan8972 / Enabling_Spikebased_Backpropagation
  ☆34Updated 5 years ago
• nmi-lab / torchneuromorphic
  Datasets recorded from Neuromorphic Sensors or Conversions using Simulations of Sensors
  ☆32Updated last year
• ykubo82 / bioCHL
  Neurons learn by predicting future activity
  ☆29Updated 4 years ago
• anilkagak2 / FPTT
  Training Recurrent Neural Networks via Forward Propagation Through Time
  ☆42Updated 4 years ago
• combra-lab / NALSM
  Neuron-Astrocyte Liquid State Machine
  ☆22Updated 3 years ago
• smonsays / equilibrium-propagation
  Fully documented Pytorch implementation of the Equilibrium Propagation algorithm.
  ☆37Updated 5 years ago
• norse / notebooks
  Notebooks illustrating the use of Norse, a library for deep-learning with spiking neural networks.
  ☆33Updated last year
• google / ihmehimmeli
  ☆143Updated 4 years ago
• kclip / snn
  Code for training binary and WTA SNNs
  ☆17Updated 3 years ago
• thomasaimondy / SBP
  The biologically plausible self backpropagation on SNNs and ANNs
  ☆12Updated 4 years ago
• sdascoli / dfa-dynamics
  ☆12Updated 4 years ago
• DimaKrotov / Dense_Associative_Memory
  Example of Dense Associative Memory training on MNIST
  ☆41Updated 3 years ago
• fzenke / pub2018superspike
  Code from our paper: SuperSpike: Supervised learning in multi-layer spiking neural networks.
  ☆58Updated 7 years ago
• jsalbert / biotorch
  BioTorch is a PyTorch framework specializing in biologically plausible learning algorithms
  ☆53Updated last year
• tavanaei / Spiking-CNN
  Spiking Convolutional Neural Networks
  ☆68Updated 6 years ago