Kai He

FidLIF: Parallel Training of High-Fidelity Spiking Neurons with Exact BPTT

Although spiking neural networks (SNNs) show promise in energy-efficient computing through event-driven computation and stateful temporal processing, their recurrent membrane dynamics render their training inherently sequential and inefficient for long sequences. Existing methods achieve full-sequence parallelism in SN...