A New Generation of Brain-Inspired Spiking Neural Networks
“This article [from an international collaboration of computer scientists and electrical engineers] serves as a tutorial and perspective showing how to apply the lessons learned from several decades of research in deep learning, gradient descent, backpropagation, and neuroscience to biologically plausible spiking neural networks (SNNs). We also explore the delicate interplay between encoding data as spikes and the learning process; the challenges and solutions of applying gradient-based learning to SNNs; the subtle link between temporal backpropagation and spike timing-dependent plasticity; and how deep learning might move toward biologically plausible online learning. . . .
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A series of companion interactive tutorials complementary to this article using our Python package, snnTorch, are also made available: HERE.“
Training Spiking Neural Networks Using Lessons From Deep Learning Jan 23. Image Credit: Proceedings of the IEEE