Adversarial Masked Graph Modeling for Robust Graph Autoencoders
This work designs a dual-consistency graph augmentation method that enriches the graph topology to mitigate structural vulnerabilities and presents an adversarial masked autoen-coder to mitigate model overfitting to the perturbed graph.
Qiqi Zhang, Chuanjin Liu, Gen Liu et al.
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