Han, Junyi

Rethinking Graph Out-Of-Distribution Generalization: A Learnable Random Walk Perspective

2025 · arXiv (Cornell University)

Out-Of-Distribution (OOD) generalization has gained increasing attentions for machine learning on graphs, as graph neural networks (GNNs) often exhibit performance degradation under distribution shifts. Existing graph OOD methods tend to follow the basic ideas of …