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Spiking neural network conversion toolbox

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b1 Documentation Status b3 b4

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] and [Rueckauer and Liu, 2018].

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