Topic: surrogate gradient flossing

Spiking Neural Networks (SNNs) promise energy efficiency and offer a more brain-like alternative to artificial neural networks. A major challenge to unleashing their potential, however, is to make them trainable on challenging tasks that require credit assignment across long time horizons. Gradient-based learning, which has driven much of the recent success in ANNs, is hampered in spiking networks by their discrete spiking interactions, which make the error landscape non-differentiable. A recent approach to this challenge is to replace the spike interaction with a surrogate gradient in the bac