A Spatial-channel-temporal-fused Attention for Spiking Neural Networks

no code implementations • 22 Sep 2022 • Wuque Cai, Hongze Sun, Rui Liu, Yan Cui, Jun Wang, Yang Xia, Dezhong Yao, Daqing Guo

Spiking neural networks (SNNs) mimic brain computational strategies, and exhibit substantial capabilities in spatiotemporal information processing.

A Synapse-Threshold Synergistic Learning Approach for Spiking Neural Networks

1 code implementation • 10 Jun 2022 • Hongze Sun, Wuque Cai, Baoxin Yang, Yan Cui, Yang Xia, Dezhong Yao, Daqing Guo

Most existing methods for training SNNs are based on the concept of synaptic plasticity; however, learning in the realistic brain also utilizes intrinsic non-synaptic mechanisms of neurons.

Event data classification Gesture Recognition +1

APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding

1 code implementation • 23 Nov 2020 • Xuhong Wang, Ding Lyu, Mengjian Li, Yang Xia, Qi Yang, Xinwen Wang, Xinguang Wang, Ping Cui, Yupu Yang, Bowen Sun, Zhenyu Guo

Limited by the time complexity of querying k-hop neighbors in a graph database, most graph algorithms cannot be deployed online and execute millisecond-level inference.

Fraud Detection Graph Embedding