Junzhou Huang*

Causal Subgraphs and Information Bottlenecks: Redefining OOD Robustness in Graph Neural Networks

"Graph Neural Networks (GNNs) are increasingly popular in processing graph-structured data, yet they face significant challenges when training and testing distributions diverge, common in real-world scenarios. This divergence often leads to substantial performance drops in GNN models. To address thi…