Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure

20 February 2019

Papers citing "Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure"

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Title
Democratizing Large Language Model-Based Graph Data Augmentation via Latent Knowledge Graphs Yushi Feng Tsai Hor Chan Guosheng Yin Lequan Yu 42 1 0 20 Feb 2025
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation Kexin Zhang Shuhan Liu Song Wang Weili Shi Chen Chen Pan Li Sheng R. Li Jundong Li Kaize Ding OOD 45 2 0 25 Oct 2024
Adversarial Training: A Survey Mengnan Zhao Lihe Zhang Jingwen Ye Huchuan Lu Baocai Yin Xinchao Wang AAML 21 0 0 19 Oct 2024
When Witnesses Defend: A Witness Graph Topological Layer for Adversarial Graph Learning Naheed Anjum Arafat D. Basu Yulia R. Gel Yuzhou Chen AAML 44 0 0 21 Sep 2024
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting Lirong Wu Haitao Lin Guojiang Zhao Cheng Tan Stan Z. Li 16 0 0 09 Sep 2024
GeoMix: Towards Geometry-Aware Data Augmentation Wen-Long Zhao Qitian Wu Chenxiao Yang Junchi Yan 27 2 0 15 Jul 2024
Explainable AI Security: Exploring Robustness of Graph Neural Networks to Adversarial Attacks Tao Wu Canyixing Cui Xingping Xian Shaojie Qiao Chao Wang Lin Yuan Shui Yu AAML 33 0 0 20 Jun 2024
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 V. Chawla Jundong Li 37 7 0 17 May 2024
IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors Shenghe Zheng Hongzhi Wang Xianglong Liu 39 3 0 02 May 2024
Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks Yassine Abbahaddou Sofiane Ennadir J. Lutzeyer Michalis Vazirgiannis Henrik Bostrom AAML OOD 24 6 0 27 Apr 2024
Uncertainty Quantification on Graph Learning: A Survey Chao Chen Chenghua Guo Rui Xu Xiangwen Liao Xi Zhang Sihong Xie Hui Xiong Philip S. Yu AI4CE 26 1 0 23 Apr 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 34 36 0 07 Mar 2024
A Simple and Yet Fairly Effective Defense for Graph Neural Networks Sofiane Ennadir Yassine Abbahaddou J. Lutzeyer Michalis Vazirgiannis Henrik Bostrom AAML 24 11 0 21 Feb 2024
Securing Graph Neural Networks in MLaaS: A Comprehensive Realization of Query-based Integrity Verification Bang Wu Xingliang Yuan Shuo Wang Qi Li Minhui Xue Shirui Pan 8 8 0 13 Dec 2023
Towards Human-like Perception: Learning Structural Causal Model in Heterogeneous Graph Tianqianjin Lin Kaisong Song Zhuoren Jiang Yangyang Kang Weikang Yuan Xurui Li Changlong Sun Cui Huang Xiaozhong Liu 28 6 0 10 Dec 2023
Exploring Graph Classification Techniques Under Low Data Constraints: A Comprehensive Study Kush Kothari Bhavya Mehta Reshmika Nambiar S. Shrawne 8 0 0 21 Nov 2023
ReConTab: Regularized Contrastive Representation Learning for Tabular Data Suiyao Chen Jing Wu N. Hovakimyan Handong Yao 29 31 0 28 Oct 2023
Promoting Generalization for Exact Solvers via Adversarial Instance Augmentation Haoyang Liu Yufei Kuang Jie Wang Xijun Li Yongdong Zhang Feng Wu AAML 31 7 0 22 Oct 2023
Data-centric Graph Learning: A Survey Jixi Liu Deyu Bo Cheng Yang Haoran Dai Qi Zhang Yixin Xiao Yufei Peng Chuan Shi GNN 16 19 0 08 Oct 2023
Addressing the Impact of Localized Training Data in Graph Neural Networks S. Akansha 22 4 0 24 Jul 2023
Adversarial Training for Graph Neural Networks: Pitfalls, Solutions, and New Directions Lukas Gosch Simon Geisler Daniel Sturm Bertrand Charpentier Daniel Zügner Stephan Günnemann AAML GNN 6 26 0 27 Jun 2023
Robust Spatiotemporal Traffic Forecasting with Reinforced Dynamic Adversarial Training Fan Liu Weijiao Zhang Haowen Liu AI4TS OOD 6 9 0 25 Jun 2023
Graph Agent Network: Empowering Nodes with Decentralized Communications Capabilities for Adversarial Resilience Ao Liu Wenshan Li Tao Li Beibei Li Hanyuan Huang Guangquan Xu Pan Zhou AAML 31 0 0 12 Jun 2023
GIMM: InfoMin-Max for Automated Graph Contrastive Learning Xin Xiong F. Shen Xiangyu Wang School of Materials Science 8 0 0 27 May 2023
IDEA: Invariant Defense for Graph Adversarial Robustness Shuchang Tao Qi Cao Huawei Shen Yunfan Wu Bingbing Xu Xueqi Cheng AAML OOD 17 6 0 25 May 2023
Distributional Signals for Node Classification in Graph Neural Networks Feng Ji See Hian Lee Kai Zhao Wee Peng Tay Jielong Yang 8 2 0 07 Apr 2023
Decentralized Adversarial Training over Graphs Ying Cao Elsa Rizk Stefan Vlaski A. H. Sayed AAML 32 1 0 23 Mar 2023
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey Yulong Wang Tong Sun Shenghong Li Xinnan Yuan W. Ni E. Hossain H. Vincent Poor AAML 18 17 0 11 Mar 2023
Multi-Agent Adversarial Training Using Diffusion Learning Ying Cao Elsa Rizk Stefan Vlaski A. H. Sayed DiffM 19 4 0 03 Mar 2023
Graph Adversarial Immunization for Certifiable Robustness Shuchang Tao Huawei Shen Qi Cao Yunfan Wu Liang Hou Xueqi Cheng AAML 4 5 0 16 Feb 2023
Revisiting Initializing Then Refining: An Incomplete and Missing Graph Imputation Network Wenxuan Tu Bin Xiao Xinwang Liu Sihang Zhou Zhiping Cai Jieren Cheng 28 5 0 15 Feb 2023
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks Jan Schuchardt Aleksandar Bojchevski Johannes Gasteiger Stephan Günnemann AAML 14 25 0 06 Feb 2023
Are Defenses for Graph Neural Networks Robust? Felix Mujkanovic Simon Geisler Stephan Günnemann Aleksandar Bojchevski OOD AAML 13 56 0 31 Jan 2023
EDoG: Adversarial Edge Detection For Graph Neural Networks Xiaojun Xu Yue Yu Hanzhang Wang Alok Lal C.A. Gunter Bo Li AAML 18 10 0 27 Dec 2022
Every Node Counts: Improving the Training of Graph Neural Networks on Node Classification Moshe Eliasof E. Haber Eran Treister GNN 22 0 0 29 Nov 2022
Spectral Adversarial Training for Robust Graph Neural Network Jintang Li Jiaying Peng Liang Chen Zibin Zheng Tingting Liang Qing Ling AAML OOD 19 17 0 20 Nov 2022
Resisting Graph Adversarial Attack via Cooperative Homophilous Augmentation Zhihao Zhu Chenwang Wu Mingyang Zhou Hao Liao DefuLian Enhong Chen AAML 8 4 0 15 Nov 2022
Model Inversion Attacks against Graph Neural Networks Zaixin Zhang Qi Liu Zhenya Huang Hao Wang Cheekong Lee Enhong AAML 8 35 0 16 Sep 2022
A Class-Aware Representation Refinement Framework for Graph Classification Jiaxing Xu Jinjie Ni Yiping Ke GNN 19 4 0 02 Sep 2022
Robust Graph Neural Networks using Weighted Graph Laplacian Bharat Runwal Vivek Sandeep Kumar AAML OOD 9 4 0 03 Aug 2022
Adversarial Camouflage for Node Injection Attack on Graphs Shuchang Tao Qi Cao Huawei Shen Yunfan Wu Liang Hou Fei Sun Xueqi Cheng AAML GNN 14 21 0 03 Aug 2022
Meta-Wrapper: Differentiable Wrapping Operator for User Interest Selection in CTR Prediction Tianwei Cao Qianqian Xu Zhiyong Yang Qingming Huang 28 6 0 28 Jun 2022
Compressing Deep Graph Neural Networks via Adversarial Knowledge Distillation Huarui He Jie Wang Zhanqiu Zhang Feng Wu 14 40 0 24 May 2022
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 23 25 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 41 98 0 16 May 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 14 123 0 18 Apr 2022
Graph Convolutional Neural Networks Sensitivity under Probabilistic Error Model Xinjue Wang Esa Ollila S. Vorobyov AAML 14 1 0 15 Mar 2022
Defending Graph Convolutional Networks against Dynamic Graph Perturbations via Bayesian Self-supervision Jun Zhuang M. Hasan AAML 18 41 0 07 Mar 2022
Model-Agnostic Augmentation for Accurate Graph Classification Jaemin Yoo Sooyeon Shim U. Kang GNN 11 29 0 21 Feb 2022
Graph Data Augmentation for Graph Machine Learning: A Survey Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng-Long Jiang OOD 12 78 0 17 Feb 2022