Spatio-temporal BP for spiking neural networks.

Python implementation of convolutional SNN.

Requirement

• Python 3.5
• Pytorch 0.4.0
• MNIST dataset

Results

After 100 epochs, it can obtain ~ 99.4% acc on MNIST.

Reference

1. Wu, Yujie, Lei Deng, Guoqi Li, Jun Zhu, and Luping Shi. "Direct Training for Spiking Neural Networks: Faster, Larger, Better." arXiv preprint arXiv:1809.05793 (2018).
2. Wu, Yujie, Lei Deng, Guoqi Li, Jun Zhu, and Luping Shi. "Spatio-temporal backpropagation for training high-performance spiking neural networks." Frontiers in neuroscience 12 (2018).