FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning

29 April 2021

Papers citing "FairDrop: Biased Edge Dropout for Enhancing Fairness in Graph Representation Learning"

21 / 21 papers shown

Title
FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training Jiaheng Liu Xiaoqian Jiang Xuzhao Li Bohan Zhang J. Zhang 32 0 0 12 Apr 2025
TiGer: Self-Supervised Purification for Time-evolving Graphs Hyeonsoo Jo Jongha Lee Fanchen Bu Kijung Shin 41 0 0 10 Mar 2025
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy Ruizhan Xue Huimin Deng Fang He Maojun Wang Zeyu Zhang 70 1 0 12 Feb 2025
MAPPING: Debiasing Graph Neural Networks for Fair Node Classification with Limited Sensitive Information Leakage Ying Song Balaji Palanisamy 80 0 0 28 Jan 2025
Unbiased GNN Learning via Fairness-Aware Subgraph Diffusion Abdullah Alchihabi Yuhong Guo DiffM 30 0 0 03 Jan 2025
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
Enhancing Fairness in Unsupervised Graph Anomaly Detection through Disentanglement Wenjing Chang Kay Liu Philip S. Yu Jianjun Yu 59 2 0 03 Jun 2024
A Comprehensive Survey on Data Augmentation Zaitian Wang Pengfei Wang Kunpeng Liu Pengyang Wang Yanjie Fu Chang-Tien Lu Charu Aggarwal Jian Pei Yuanchun Zhou ViT 109 22 0 15 May 2024
Better Fair than Sorry: Adversarial Missing Data Imputation for Fair GNNs Debolina Halder Lina Arlei Silva 26 0 0 02 Nov 2023
Deceptive Fairness Attacks on Graphs via Meta Learning Jian Kang Yinglong Xia Ross Maciejewski Jiebo Luo Hanghang Tong 42 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 43 3 0 20 Oct 2023
A Survey of Imbalanced Learning on Graphs: Problems, Techniques, and Future Directions Zemin Liu Yuan N. Li Nan-Fang Chen Qian Wang Bryan Hooi Bin He FaML 14 13 0 26 Aug 2023
CAFIN: Centrality Aware Fairness inducing IN-processing for Unsupervised Representation Learning on Graphs A. Arvindh Aakash Aanegola Amul Agrawal Ramasuri Narayanam Ponnurangam Kumaraguru 24 0 0 10 Apr 2023
Drop Edges and Adapt: a Fairness Enforcing Fine-tuning for Graph Neural Networks Indro Spinelli Riccardo Bianchini Simone Scardapane 26 1 0 22 Feb 2023
Data Augmentation on Graphs: A Technical Survey Jiajun Zhou Chenxuan Xie Shengbo Gong Z. Wen Xiangyu Zhao Qi Xuan Xiaoniu Yang AI4TS 24 8 0 20 Dec 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
Graph Data Augmentation for Graph Machine Learning: A Survey Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng Jiang OOD 30 79 0 17 Feb 2022
Obtaining Dyadic Fairness by Optimal Transport Moyi Yang Junjie Sheng Xiangfeng Wang Wenyan Liu Bo Jin Jun Wang H. Zha 27 6 0 09 Feb 2022
A Survey on Bias and Fairness in Machine Learning Ninareh Mehrabi Fred Morstatter N. Saxena Kristina Lerman Aram Galstyan SyDa FaML 332 4,223 0 23 Aug 2019
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 261 3,240 0 24 Nov 2016