43 citations · 109 across the 12 of their papers we have counts for
12 papers
Spike-driven Transformer V2: Meta Spiking Neural Network Architecture Inspiring the Design of Next-generation Neuromorphic Chips
Man Yao, Jiakui Hu, Tianxiang Hu +5
Neuromorphic computing, which exploits Spiking Neural Networks (SNNs) on neuromorphic chips, is a promising energy-efficient alternative to traditional AI. CNN-based SNNs are the c…
SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence
Wei Fang, Yanqi Chen, Jianhao Ding +7
Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic chips with high energy efficiency by introducing neural dynamics and spike properties. As…
NP-Hardness of Tensor Network Contraction Ordering
Jianyu Xu, Hanwen Zhang, Ling Liang +3
We study the optimal order (or sequence) of contracting a tensor network with a minimal computational cost. We conclude 2 different versions of this optimal sequence: that minimize…
Inherent Redundancy in Spiking Neural Networks
Man Yao, Jiakui Hu, Guangshe Zhao +4
Spiking Neural Networks (SNNs) are well known as a promising energy-efficient alternative to conventional artificial neural networks. Subject to the preconceived impression that SN…
Deep Directly-Trained Spiking Neural Networks for Object Detection
Qiaoyi Su, Yuhong Chou, Yifan Hu +4
Spiking neural networks (SNNs) are brain-inspired energy-efficient models that encode information in spatiotemporal dynamics. Recently, deep SNNs trained directly have shown great…
Theoretical foundations of studying criticality in the brain
Yang Tian, Zeren Tan, Hedong Hou +6
Criticality is hypothesized as a physical mechanism underlying efficient transitions between cortical states and remarkable information processing capacities in the brain. While co…