Operational Feature Fingerprints of Graph Datasets via a White-Box Signal-Subspace Probe

Key Takeaway

You can diagnose what graph datasets require and why GNNs work by replacing learned message passing with interpretable signal components—this white-box approach is competitive with black-box models while revealing which graph properties (smoothing, raw features, class geometry) matter most.