Spiking Neural Network (SNN) with PyTorch: towards bridging the gap between deep learning and the human brain

I think I’ve discovered something amazing: Hebbian learning naturally takes place during the backpropagation of SNNs. Backpropagation in Spiking Neural Networks (SNNs) engenders Spike-Timing-Dependent Plasticity (STDP)-like Hebbian learning behavior. So: – At first I simply thought “hey, what about coding a Spiking Neural Network using an automatic differentiation framework?” Here it is. – Then I … Continue reading Spiking Neural Network (SNN) with PyTorch: towards bridging the gap between deep learning and the human brain