Our results emphasize the importance of domain diversity and domain invariant learning for robust generalization. This work fills a key gap in existing research on graph domain generalization and lays ...

Abstract: Graph Meta-learning methods have improved the performance of few-shot node classification by means of applying meta-learning to the data in non-Euclidean domains. However, most works focus ...