Shu-Xia Lu

Topology-aware dynamic co-evolution for robust graph learning.

Graph Neural Networks (GNNs) have achieved remarkable success in learning from graph-structured data. However, recent studies have revealed their vulnerability to adversarial attacks, where imperceptible perturbations to the graph structure can easily mislead predictions. Existing defense methods predominantly rely on...