2025
Schoenberg Kernel Loss for Spiking Neural Network Training
ICASSP 2025accepted
In this paper, we propose the Schoenberg kernel loss, a loss function that measures the divergence between spike trains for spiking neural network training. Our method addresses the challenges of non-differentiable spiking neurons and leverages both spatial and temporal dynamics in information proce…