Topology Attack and Defense for Graph Neural Networks: An Optimization
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Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective

10 June 2019

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Papers citing "Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective"

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Title
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review Han Xu Yao Ma Haochen Liu Debayan Deb Hui Liu Jiliang Tang Anil K. Jain AAML 79 680 0 17 Sep 2019
Transferring Robustness for Graph Neural Network Against Poisoning Attacks Xianfeng Tang Yandong Li Yiwei Sun Huaxiu Yao P. Mitra Suhang Wang OOD AAML 110 184 0 20 Aug 2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models Heng Chang Yu Rong Tingyang Xu Wenbing Huang Honglei Zhang Peng Cui Wenwu Zhu Junzhou Huang AAML 70 155 0 04 Aug 2019
On the Design of Black-box Adversarial Examples by Leveraging Gradient-free Optimization and Operator Splitting Method Pu Zhao Sijia Liu Pin-Yu Chen Nghia Hoang Kaidi Xu B. Kailkhura Xue Lin AAML 119 54 0 26 Jul 2019
Stability Properties of Graph Neural Networks Fernando Gama Joan Bruna Alejandro Ribeiro 109 236 0 11 May 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan Xinyu Lin AAML FAtt 140 43 0 03 Apr 2019
Adversarial Robustness vs Model Compression, or Both? Shaokai Ye Kaidi Xu Sijia Liu Jan-Henrik Lambrechts Huan Zhang Aojun Zhou Kaisheng Ma Yanzhi Wang Xue Lin AAML 98 165 0 29 Mar 2019
Adversarial Attack and Defense on Graph Data: A Survey Lichao Sun Yingtong Dou Carl Yang Ji Wang Yixin Liu Philip S. Yu Lifang He Yangqiu Song GNN AAML 139 286 0 26 Dec 2018