Cheng-Hu Xi

Implicit Feature Reweighting for Label-Free Graph Generalization

Graph-level out-of-distribution (OOD) generalization is critical for deploying graph neural networks in real-world applications where distribution shifts are inevitable. Existing approaches typically require class labels during representation learning to decide which substructures are predictive, limiting their applica...