Community-aware sparse topology design for efficient spiking neural networks.
This work proposes a community-aware sparse topology design framework for graph-based SNNs and challenges the prevailing assumption that network size or sparsity alone is sufficient, demonstrating that how sparse connections are organized - the graph topology - critically influences learning efficiency, accuracy, and e...