2 papers
cs.NE2026
Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients
Feifan Zhou, Xiang Wei, Yang Liu +1
Spiking Neural Networks (SNNs) have emerged with promising energy-efficient property, yet a substantial performance gap persists compared to Artificial Neural Networks (ANNs). This…
q-bio.NC2025
HetSyn: Versatile Timescale Integration in Spiking Neural Networks via Heterogeneous Synapses
Zhichao Deng, Zhikun Liu, Junxue Wang +3
Spiking Neural Networks (SNNs) offer a biologically plausible and energy-efficient framework for temporal information processing. However, existing studies overlook a fundamental p…