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Shuxun Wang

2 accepted papers

2025

DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks

ICLR 2025poster

Spiking Neural Networks (SNNs), with their biologically inspired spatio-temporal dynamics and spike-driven processing, are emerging as a promising low-power alternative to traditional Artificial Neural Networks (ANNs). However, the complex neuronal dynamics and non-differentiable spike communication…

Cited by 0SourcePDFScholar
2025

Towards More Discriminative Feature Learning in SNNs with Temporal-Self-Erasing Supervision

AAAI 2025technical

Spiking Neural Networks (SNNs) are biologically inspired models that process visual inputs over multiple time steps. However, they often struggle with limited feature discrimination along the temporal dimension due to inherent spatiotemporal invariance. This limitation arises from the redundant acti…

Cited by 0SourcePDFScholar