A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy,
Robustness, Fairness, and Explainability

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

18 April 2022

Papers citing "A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability"

15 / 15 papers shown

Title
Robustness questions the interpretability of graph neural networks: what to do? Kirill Lukyanov Georgii Sazonov Serafim Boyarsky Ilya Makarov AAML 36 0 0 05 May 2025
FedHERO: A Federated Learning Approach for Node Classification Task on Heterophilic Graphs Zihan Chen Xingbo Fu Yushun Dong Jundong Li Cong Shen FedML 62 0 0 29 Apr 2025
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 34 98 0 16 May 2022
Learning Robust Representation through Graph Adversarial Contrastive Learning Jiayan Guo Shangyang Li Yue Zhao Yan Zhang 12 5 0 31 Jan 2022
Releasing Graph Neural Networks with Differential Privacy Guarantees Iyiola E. Olatunji Thorben Funke Megha Khosla 19 31 0 18 Sep 2021
Trustworthy AI: A Computational Perspective Haochen Liu Yiqi Wang Wenqi Fan Xiaorui Liu Yaxin Li Shaili Jain Yunhao Liu Anil K. Jain Jiliang Tang FaML 87 193 0 12 Jul 2021
Membership Inference Attack on Graph Neural Networks Iyiola E. Olatunji Wolfgang Nejdl Megha Khosla AAML 18 77 0 17 Jan 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 156 463 0 31 Dec 2020
GraphFL: A Federated Learning Framework for Semi-Supervised Node Classification on Graphs Binghui Wang Ang Li H. Li Yiran Chen 65 94 0 08 Dec 2020
Model Extraction Attacks on Graph Neural Networks: Taxonomy and Realization Bang Wu Xiangwen Yang Shirui Pan Xingliang Yuan MIACV MLAU 36 47 0 24 Oct 2020
Stealing Links from Graph Neural Networks Xinlei He Jinyuan Jia Michael Backes Neil Zhenqiang Gong Yang Zhang AAML 51 164 0 05 May 2020
Heterogeneous Graph Transformer Ziniu Hu Yuxiao Dong Kuansan Wang Yizhou Sun 167 1,157 0 03 Mar 2020
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 283 4,143 0 23 Aug 2019
Learning Adversarially Fair and Transferable Representations David Madras Elliot Creager T. Pitassi R. Zemel FaML 205 663 0 17 Feb 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 152 1,748 0 02 Mar 2017