Towards a Unified Framework for Fair and Stable Graph Representation Learning

25 February 2021

Himabindu Lakkaraju

Papers citing "Towards a Unified Framework for Fair and Stable Graph Representation Learning"

39 / 39 papers shown

Title
Causally Fair Node Classification on Non-IID Graph Data Yucong Dai Lu Zhang Yaowei Hu Susan Gauch Yongkai Wu FaML 50 0 0 03 May 2025
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage Ying Song Balaji Palanisamy 78 0 0 28 Jan 2025
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion Abdullah Alchihabi Yuhong Guo DiffM 30 0 0 03 Jan 2025
ComFairGNN: Community Fair Graph Neural Network Yonas Sium Qi Li 31 0 0 07 Nov 2024
Reproducibility Study Of Learning Fair Graph Representations Via Automated Data Augmentations Thijmen Nijdam Juell Sprott Taiki Papandreou-Lazos Jurgen de Heus 29 0 0 31 Aug 2024
CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models Song Wang Peng Wang Tong Zhou Yushun Dong Zhen Tan Jundong Li CoGe 56 7 0 02 Jul 2024
Reproducibility study of FairAC Gijs de Jong Macha J. Meijer Derck W. E. Prinzhorn Harold Ruiter 30 0 0 05 Jun 2024
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement Wenjing Chang Kay Liu Philip S. Yu Jianjun Yu 57 2 0 03 Jun 2024
On Explaining Unfairness: An Overview Christos Fragkathoulas Vasiliki Papanikou Danae Pla Karidi E. Pitoura XAI FaML 19 2 0 16 Feb 2024
Use of Graph Neural Networks in Aiding Defensive Cyber Operations Shaswata Mitra Trisha Chakraborty Subash Neupane Aritran Piplai Sudip Mittal AAML 42 3 0 11 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 49 2 0 19 Dec 2023
Better Fair than Sorry: Adversarial Missing Data Imputation for Fair GNNs Debolina Halder Lina Arlei Silva 23 0 0 02 Nov 2023
Deceptive Fairness Attacks on Graphs via Meta Learning Jian Kang Yinglong Xia Ross Maciejewski Jiebo Luo Hanghang Tong 36 4 0 24 Oct 2023
Adversarial Attacks on Fairness of Graph Neural Networks Binchi Zhang Yushun Dong Chen Chen Yada Zhu Minnan Luo Jundong Li 41 3 0 20 Oct 2023
Weisfeiler and Leman Go Measurement Modeling: Probing the Validity of the WL Test Arjun Subramonian Adina Williams Maximilian Nickel Yizhou Sun Levent Sagun 28 0 0 11 Jul 2023
On Performance Discrepancies Across Local Homophily Levels in Graph Neural Networks Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T. Shaub Danai Koutra 30 5 0 08 Jun 2023
GFairHint: Improving Individual Fairness for Graph Neural Networks via Fairness Hint Paiheng Xu Yuhang Zhou Bang An Wei Ai Furong Huang 22 6 0 25 May 2023
A Comprehensive Survey on Deep Graph Representation Learning Wei Ju Zheng Fang Yiyang Gu Zequn Liu Qingqing Long ... Jingyang Yuan Yusheng Zhao Yifan Wang Xiao Luo Ming Zhang GNN AI4TS 51 141 0 11 Apr 2023
Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach Zhimeng Jiang Xiaotian Han Hongye Jin Guanchu Wang Rui Chen Na Zou Xia Hu 12 13 0 06 Mar 2023
Unraveling Privacy Risks of Individual Fairness in Graph Neural Networks He Zhang Xingliang Yuan Shirui Pan 30 11 0 30 Jan 2023
RELIANT: Fair Knowledge Distillation for Graph Neural Networks Yushun Dong Binchi Zhang Yiling Yuan Na Zou Qi Wang Jundong Li 82 13 0 03 Jan 2023
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution Yushun Dong Song Wang Jing Ma Ninghao Liu Jundong Li 42 21 0 25 Nov 2022
BiaScope: Visual Unfairness Diagnosis for Graph Embeddings Agapi Rissaki Bruno Scarone David Liu Aditeya Pandey Brennan Klein Tina Eliassi-Rad M. Borkin FaML 18 6 0 12 Oct 2022
Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative Tianxin Wei Yuning You Tianlong Chen Yang Shen Jingrui He Zhangyang Wang 29 45 0 07 Oct 2022
Evaluating Explainability for Graph Neural Networks Chirag Agarwal Owen Queen Himabindu Lakkaraju Marinka Zitnik 51 99 0 19 Aug 2022
On Graph Neural Network Fairness in the Presence of Heterophilous Neighborhoods Donald Loveland Jiong Zhu Mark Heimann Benjamin Fish Michael T. Schaub Danai Koutra 27 6 0 10 Jul 2022
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage Yu-Chiang Frank Wang Yuying Zhao Yushun Dong Huiyuan Chen Jundong Li Tyler Derr 17 80 0 07 Jun 2022
FairNorm: Fair and Fast Graph Neural Network Training Öykü Deniz Köse Yanning Shen AI4CE 16 4 0 20 May 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Fairness in Graph Mining: A Survey Yushun Dong Jing Ma Song Wang Chen Chen Jundong Li FaML 34 112 0 21 Apr 2022
FairEGM: Fair Link Prediction and Recommendation via Emulated Graph Modification Sean Current Yuntian He Saket Gurukar Srinivas Parthasarathy 28 13 0 27 Jan 2022
FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing Donald Loveland Jiayi Pan A. Bhathena Yiyang Lu 13 16 0 10 Jan 2022
Releasing Graph Neural Networks with Differential Privacy Guarantees Iyiola E. Olatunji Thorben Funke Megha Khosla 32 44 0 18 Sep 2021
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks Yushun Dong Ninghao Liu B. Jalaeian Jundong Li 28 117 0 11 Aug 2021
Probing GNN Explainers: A Rigorous Theoretical and Empirical Analysis of GNN Explanation Methods Chirag Agarwal Marinka Zitnik Himabindu Lakkaraju 27 51 0 16 Jun 2021
Fairness-Aware Node Representation Learning Öykü Deniz Köse Yanning Shen 14 22 0 09 Jun 2021
Heterogeneous Graph Transformer Ziniu Hu Yuxiao Dong Kuansan Wang Yizhou Sun 185 1,170 0 03 Mar 2020
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 267 1,944 0 09 Jun 2018
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments Alexandra Chouldechova FaML 207 2,084 0 24 Oct 2016