Topology Awareness and Generalization Performance of Graph Neural Networks

The author explores the relationship between topology awareness and generalization performance in Graph Neural Networks, revealing insights on structural subgroup generalization and fairness. The framework connects structural awareness with approximate metric embedding, offering a new perspective on GNN capabilities.