Cure-GNN: A Robust Curvature-Enhanced Graph Neural Network Against Adversarial Attacks - researchr publication related

researchr

You are not signed in
Sign in
Sign up

Yang Xiao 0014, Zhuolin Xing, Alex X. Liu, Lei Bai 0001, Qingqi Pei, Lina Yao 0001. Cure-GNN: A Robust Curvature-Enhanced Graph Neural Network Against Adversarial Attacks. IEEE Trans. Dependable Sec. Comput., 20(5):4214-4229, September - October 2023. [doi]

The following publications are possibly variants of this publication:

Understanding the robustness of graph neural networks against adversarial attacksTao Wu 0003, Canyixing Cui, Xingping Xian, Shaojie Qiao, Chao Wang 0025, Lin Yuan 0002, Shui Yu 0001. kbs, 323:113714, 2025. [doi]

Robust Graph Convolutional Networks Against Adversarial AttacksDingyuan Zhu, Ziwei Zhang, Peng Cui 0001, Wenwu Zhu 0001. kdd 2019: 1399-1407 [doi]

Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial AttacksXin Zhao, Zeru Zhang, Zijie Zhang, Lingfei Wu, Jiayin Jin, Yang Zhou, Ruoming Jin, Dejing Dou, Da Yan 0001. icml 2021: 12719-12735 [doi]

Graph Structure Reshaping Against Adversarial Attacks on Graph Neural NetworksHaibo Wang 0004, Chuan Zhou 0001, Xin Chen, Jia Wu 0001, Shirui Pan, Zhao Li 0007, Jilong Wang 0001, Philip S. Yu. tkde, 36(11):6344-6357, November 2024. [doi]

runs on WebDSL