Papers citing 'GraphDefense: Towards Robust Graph Convolutional Networks'

Title
Safety in Graph Machine Learning: Threats and Safeguards Song Wang Yushun Dong Binchi Zhang Zihan Chen Xingbo Fu Yinhan He Cong Shen Chuxu Zhang Nitesh Chawla Wenlin Yao 148 10 0 17 May 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Mohit Bansal AI4CE 206 1 0 23 Apr 2024
Self-supervised Heterogeneous Graph Variational AutoencodersKnowledge Discovery and Data Mining (KDD), 2023 Yige Zhao Jianxiang Yu Yao Cheng Chengcheng Yu Yiding Liu Xiang Li Shuaiqiang Wang BDL 30 1 0 14 Nov 2023
Decentralized Adversarial Training over GraphsIEEE Transactions on Information Theory (IEEE Trans. Inf. Theory), 2023 Ying Cao Elsa Rizk Stefan Vlaski Ali H. Sayed AAML 301 3 0 23 Mar 2023
Multi-Agent Adversarial Training Using Diffusion LearningIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2023 Ying Cao Elsa Rizk Stefan Vlaski Ali H. Sayed DiffM 143 4 0 03 Mar 2023
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and ExplainabilityMachine Intelligence Research (MIR), 2022 Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Shucheng Zhou Suhang Wang 209 177 0 18 Apr 2022
Graph Convolutional Neural Networks Sensitivity under Probabilistic Error ModelIEEE Transactions on Signal and Information Processing over Networks (TSIPN), 2022 Xinjue Wang Esa Ollila S. Vorobyov AAML 184 3 0 15 Mar 2022
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervisionAAAI Conference on Artificial Intelligence (AAAI), 2022 Jun Zhuang M. Hasan AAML 125 45 0 07 Mar 2022
Graph Data Augmentation for Graph Machine Learning: A SurveyIEEE Data Engineering Bulletin (DEB), 2022 Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng Jiang OOD 197 92 0 17 Feb 2022
Data Augmentation for Deep Graph Learning: A SurveySIGKDD Explorations (SIGKDD Explor.), 2022 Kaize Ding Zhe Xu Hanghang Tong Huan Liu OOD GNN 169 256 0 16 Feb 2022
Learning Robust Representation through Graph Adversarial Contrastive LearningInternational Conference on Database Systems for Advanced Applications (DASFAA), 2022 Jiayan Guo Shangyang Li Yue Zhao Fei Huang 111 8 0 31 Jan 2022
Model Stealing Attacks Against Inductive Graph Neural Networks Yun Shen Xinlei He Yufei Han Yang Zhang 144 76 0 15 Dec 2021
On Generalization of Graph Autoencoders with Adversarial Training Tianjin Huang Yulong Pei Vlado Menkovski Mykola Pechenizkiy GNN 163 6 0 06 Jul 2021
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization PerspectiveWeb Search and Data Mining (WSDM), 2021 Lun Du Xu Chen Fei Gao Qiang Fu Kunqing Xie Shi Han Dongmei Zhang 168 13 0 17 May 2021
IA-GCN: Interpretable Attention based Graph Convolutional Network for Disease prediction Anees Kazi Soroush Farghadani Nassir Navab GNN 122 18 0 29 Mar 2021
Unsupervised Adversarially-Robust Representation Learning on GraphsAAAI Conference on Artificial Intelligence (AAAI), 2020 Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Luke Huan SSL AAML OOD 278 41 0 04 Dec 2020
A Survey of Adversarial Learning on Graphs Liang Chen Jintang Li Jiaying Peng Tao Xie Zengxu Cao Kun Xu Xiangnan He Zibin Zheng Bingzhe Wu AAML 155 89 0 10 Mar 2020
Adversarial Attacks and Defenses on Graphs: A Review, A Tool and Empirical Studies Wei Jin Yaxin Li Han Xu Yiqi Wang Shuiwang Ji Charu C. Aggarwal Shucheng Zhou AAML GNN 194 105 0 02 Mar 2020
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 268 337 0 26 Dec 2018