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cs.LG2023
Towards Inductive Robustness: Distilling and Fostering Wave-induced Resonance in Transductive GCNs Against Graph Adversarial Attacks
Ao Liu, Wenshan Li, Tao Li +3
Graph neural networks (GNNs) have recently been shown to be vulnerable to adversarial attacks, where slight perturbations in the graph structure can lead to erroneous predictions.…
cs.LG2023
Graph Agent Network: Empowering Nodes with Inference Capabilities for Adversarial Resilience
Ao Liu, Wenshan Li, Tao Li +5
End-to-end training with global optimization have popularized graph neural networks (GNNs) for node classification, yet inadvertently introduced vulnerabilities to adversarial edge…