Spiking neural networks are not currently the focus of most machine learning researchers, but there are several reasons why they are of interest:

• Spike based communication is believed to be the primary way in which biological neutrons interact, so spiking neuron models are of interest to computational neuroscientists.

• Special purpose hardware (often called brain-inspired or neuromorphic hardware) can potentially deliver better power / performance numbers than deep learning hardware accelerators.

With that being said there are few modern machine learning focussed libraries available to explore spiking neural networks. We are in the early stages of creating one based on PyTorch (https://github.com/norse/norse). What we’ve publicly published is enough to explore supervised learning on small datasets like MNIST and CIFAR-10.

Any feedback or comments would be appreciated. Also happy to discuss related state of the art research.