Topology-aware GNNs under structural perturbations: Empirical robustness across domains
Results support a conditional empirical conclusion: combining structure, topology, and stability-oriented training can improve robustness under specified structural perturbations, with dataset-dependent accuracy–stability trade-offs rather than universal guarantees.
Jelena Losic, Charles Fanning
· PLOS Complex Systems · 0 citations