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A curated list of materials for Spiking Neural Networks, 3rd generation of artificial neural networks.

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Books :closed_book:Papers :page_with_curl:Frameworks :computer:Repositories :open_file_folder:Others :memo:

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What's inside

Papers :page_with_curl:

Frameworks :computer:

  • BindsNET

    Python framework for simulation of spiking neural networks using Pytorch.

  • Brian2

    python simulator for spiking neural networks.

  • NengoDL

    library for building, testing and deploying neural networks, especially spiking neural networks.

  • NEST

    spiking neural network simulator with focus on dynamics, size and structure of neural systems. Can be complemented by PyNN.

  • Norse

    framework for spiking neural networks, which expands PyTorch with SNN primitives.

  • PyNN

    library for defining neural models independent of simulator specifics.

Repositories :open_file_folder:

  • BrainPy

    simulation toolbox for computational neuroscience research.

  • hybrid-snn-conversion

    hybrid ann to snn conversion with spike-based backpropagation.

  • snn-toolbox

    toolbox for conversion of ANNs into SNNs using weight normalization.

  • spikeflow

    library for spiking neural networks on top of Tensorflow.

  • SpikingJelly

    new simple SNN framework in Pytorch with easy SNN initialization and ANN2SNN conversion.

Books :closed_book:

Others :memo:

Showing a sample of 56 resources. View the full list on GitHub →