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cs.LG2025
Unifying Adversarial Perturbation for Graph Neural Networks
Jinluan Yang, Ruihao Zhang, Zhengyu Chen +2
This paper studies the vulnerability of Graph Neural Networks (GNNs) to adversarial attacks on node features and graph structure. Various methods have implemented adversarial train…
cs.LG2023
Learning to Reweight for Graph Neural Network
Zhengyu Chen, Teng Xiao, Kun Kuang +6
Graph Neural Networks (GNNs) show promising results for graph tasks. However, existing GNNs' generalization ability will degrade when there exist distribution shifts between testin…