Exploiting Spatial-temporal Data for Sleep Stage Classification via Hypergraph Learning

no code implementations • 5 Sep 2023 • Yuze Liu, Ziming Zhao, Tiehua Zhang, Kang Wang, Xin Chen, Xiaowei Huang, Jun Yin, Zhishu Shen

Sleep stage classification is crucial for detecting patients' health conditions.

Classification

Learning from Heterogeneity: A Dynamic Learning Framework for Hypergraphs

no code implementations • 7 Jul 2023 • Tiehua Zhang, Yuze Liu, Zhishu Shen, Xingjun Ma, Xin Chen, Xiaowei Huang, Jun Yin, Jiong Jin

Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data.

Graph Learning Link Prediction +1

An Adaptive Federated Relevance Framework for Spatial Temporal Graph Learning

no code implementations • 7 Jun 2022 • Tiehua Zhang, Yuze Liu, Zhishu Shen, Rui Xu, Xin Chen, Xiaowei Huang, Xi Zheng

Spatial-temporal data contains rich information and has been widely studied in recent years due to the rapid development of relevant applications in many fields.

Federated Learning Graph Learning