Graph Classification

Graph classification — predicting a label for an entire graph, not individual nodes — matters for molecular screening, social network analysis, and program verification. GIN (Xu et al., 2019) formalized the connection between GNN expressiveness and the Weisfeiler-Leman graph isomorphism test, and the TU datasets became standard benchmarks. Recent work on graph transformers (GPS, Exphormer) and higher-order GNNs pushes beyond WL limits, while OGB's ogbg-molhiv and ogbg-molpcba provide more rigorous large-scale evaluation than the classic small-graph benchmarks.