Yu-Qin Huang

Moving beyond graph homophily: Disentangled node representation for graph neural networks.

Graph Neural Networks (GNNs) have demonstrated strong performance on graph-structured data through neighborhood aggregation. However, they often underperform on heterophilic graphs and suffer from over-smoothing, leading to suboptimal representations. We attribute these limitations to the lack of view-specific factoriz...