1 citations · 1 across the 3 of their papers we have counts for
5 papers
Proofs and disproofs of some conjectures on zero-sum problems of new types
Yang Li, San Ling, Zhonghua Sun +1
For integers and , let be the least such that every sequence of vectors in , each nonzero modulo , contains terms whose sum is zero mod…
Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training
Xiaochen Zhao, Chengting Yu, Kairong Yu +2
Spiking Neural Networks (SNNs) exhibit exceptional energy efficiency on neuromorphic hardware due to their sparse activation patterns. However, conventional training methods based…
Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacement
Shu Yang, Chengting Yu, Lei Liu +3
Spiking Neural Networks (SNNs) have garnered considerable attention as a potential alternative to Artificial Neural Networks (ANNs). Recent studies have highlighted SNNs' potential…
Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment
Chengting Yu, Xiaochen Zhao, Lei Liu +4
Spiking Neural Networks (SNNs) are emerging as a brain-inspired alternative to traditional Artificial Neural Networks (ANNs), prized for their potential energy efficiency on neurom…
Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
Chengting Yu, Lei Liu, Gaoang Wang +2
Recent insights have revealed that rate-coding is a primary form of information representation captured by surrogate-gradient-based Backpropagation Through Time (BPTT) in training…