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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 <http://snntoolbox.readthedocs.io>_ for a complete user guide and API reference. See also the accompanying articles [Rueckauer et al., 2017] <https://www.frontiersin.org/articles/10.3389/fnins.2017.00682/abstract>, [Rueckauer and Liu, 2018] <https://ieeexplore.ieee.org/abstract/document/8351295/>, and [Rueckauer and Liu, 2021] <https://ieeexplore.ieee.org/abstract/document/9533837>_.