K. Santosh

SAGE: Surrogate-gradient Adaptation via Attention-Guided Entropy for Spiking Transformers

Spiking neural networks (SNNs) offer an energy-efficient alternative to conventional deep neural networks by exploiting sparse event-driven computation, but their training remains challenging because the non-differentiable spike function requires surrogate gradients whose fixed shape may be suboptimal across layers and...