4 papers
Hypergraph Neural Diffusion: A PDE-Inspired Framework for Hypergraph Message Passing
Zhiheng Zhou, Mengyao Zhou, Xixun Lin +2
Hypergraph neural networks (HGNNs) have shown remarkable potential in modeling high-order relationships that naturally arise in many real-world data domains. However, existing HGNN…
Tackling Over-smoothing on Hypergraphs: A Ricci Flow-guided Neural Diffusion Approach
Mengyao Zhou, Zhiheng Zhou, Xiao Han +3
Hypergraph neural networks (HGNNs) have demonstrated strong capabilities in modeling complex higher-order relationships. However, existing HGNNs often suffer from over-smoothing as…
Extracting Interpretable Higher-Order Topological Features across Multiple Scales for Alzheimer's Disease Classification
Dengyi Zhao, Shanyong Li, Yunping Wang +4
Brain network topology, derived from functional magnetic resonance imaging (fMRI), holds promise for improving Alzheimer's disease (AD) diagnosis. Current methods primarily focus o…
HOI-Brain: a novel multi-channel transformers framework for brain disorder diagnosis by accurately extracting signed higher-order interactions from fMRI
Dengyi Zhao, Zhiheng Zhou, Guiying Yan +2
Accurately characterizing higher-order interactions of brain regions and extracting interpretable organizational patterns from Functional Magnetic Resonance Imaging data is crucial…