Debiasing Graph Neural Networks via Learning Disentangled Causal
Substructure

Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure

28 September 2022

Jian Tang

Papers citing "Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure"

15 / 15 papers shown

Title
A Causal Adjustment Module for Debiasing Scene Graph Generation Li Liu Shuzhou Sun Shuaifeng Zhi Fan Shi Zhen Liu J. Heikkilä Yongxiang Liu CML 52 2 0 22 Mar 2025
SSL Framework for Causal Inconsistency between Structures and Representations Hang Chen Xinyu Yang Keqing Du Wenya Wang 50 2 0 03 Jan 2025
Causal-aware Graph Neural Architecture Search under Distribution Shifts Peiwen Li Xin Wang Zeyang Zhang Yi Qin Ziwei Zhang Jialong Wang Yang Li Wenwu Zhu CML OOD 55 4 0 31 Dec 2024
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs Bowen Liu Haoyang Li Shuning Wang Shuo Nie Shanghang Zhang OODD CML 58 0 0 29 Oct 2024
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
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 37 2 0 03 Aug 2024
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Graph Neural Networks Jiahua Rao Jiancong Xie Hanjing Lin Shuangjia Zheng Zhen Wang Yuedong Yang 19 0 0 07 Feb 2024
Graph Fairness Learning under Distribution Shifts Yibo Li Xiao Wang Yujie Xing Shaohua Fan Ruijia Wang Yaoqi Liu Chuan Shi OOD 23 7 0 30 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 24 2 0 19 Dec 2023
Enhancing the Performance of Neural Networks Through Causal Discovery and Integration of Domain Knowledge Xiaoge Zhang Xiao-Lin Wang Fenglei Fan Yiu-ming Cheung Indranil Bose 18 1 0 29 Nov 2023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 19 33 0 29 Oct 2023
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 23 5 0 30 Nov 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 89 222 0 30 Jan 2022
Generalizing Graph Neural Networks on Out-Of-Distribution Graphs Shaohua Fan Xiao Wang Chuan Shi Peng Cui Bai Wang CML OOD OODD AI4CE 37 81 0 20 Nov 2021
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 110 142 0 05 Feb 2021