https://github.com/neuromorphicprocessorproject/snn_toolbox

Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.
https://github.com/neuromorphicprocessorproject/snn_toolbox

brian brian2 caffe deep-learning deep-neural-networks keras lasagne loihi nest pynn pytorch spiking-neural-networks spinnaker tensorflow

Last synced: 25 days ago
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Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

• Host: GitHub
• URL: https://github.com/neuromorphicprocessorproject/snn_toolbox
• Owner: NeuromorphicProcessorProject
• License: mit
• Created: 2016-07-27T07:58:19.000Z (over 8 years ago)
• Default Branch: master
• Last Pushed: 2023-01-13T10:01:01.000Z (almost 2 years ago)
• Last Synced: 2024-10-11T18:20:56.472Z (25 days ago)
• Topics: brian, brian2, caffe, deep-learning, deep-neural-networks, keras, lasagne, loihi, nest, pynn, pytorch, spiking-neural-networks, spinnaker, tensorflow
• Language: Python
• Size: 338 MB
• Stars: 360
• Watchers: 16
• Forks: 105
• Open Issues: 3
• Metadata Files:
  • Readme: README.rst
  • Changelog: CHANGELOG.rst
  • License: LICENSE.txt

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Spiking neural network conversion toolbox

=========================================

The SNN conversion toolbox (SNN-TB) is a framework to transform rate-based

artificial neural networks into spiking neural networks, and to run them using

various spike encodings. A unique feature about SNN-TB is that it accepts input

models from many different deep-learning libraries (Keras / TF, pytorch, ...)

and provides an interface to several backends for simulation (pyNN, brian2,

...) or deployment (SpiNNaker, Loihi).

Please

refer to the `Documentation `_ for a complete

user guide and API reference. See also the accompanying articles

`[Rueckauer et al., 2017] `_, `[Rueckauer and Liu, 2018] `_, and `[Rueckauer and Liu, 2021] `_.