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A deep learning library for spiking neural networks which is based on PyTorch, focuses on fast training and supports inference on neuromorphic hardware.
Sinabs (Sinabs Is Not A Brain Simulator) is a python library for the development and implementation of Spiking Convolutional Neural Networks (SCNNs).
The library implements several layers that are spiking equivalents of CNN layers.
In addition it provides support to import CNN models implemented in torch conveniently to test their spiking equivalent implementation.
This project is managed by SynSense (former aiCTX AG).
The sinabs-dynapcnn was incorporated to this project, and it enables porting sinabs models to chips and dev-kits with DYNAP-CNN technology.
In case you find this software library useful for your work please consider citing it as follows:
@software{sinabs,
author = {Sheik, Sadique and Lenz, Gregor and Bauer, Felix and Kuepelioglu, Nogay },
doi = {10.5281/zenodo.8385545},
license = {Apache-2.0},
title = {{SINABS: A simple Pytorch based SNN library specialised for Speck}},
url = {https://github.com/synsense/sinabs}
}
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A deep learning library for spiking neural networks which is based on PyTorch, focuses on fast training and supports inference on neuromorphic hardware.