Debiased Graph Neural Networks with Agnostic Label Selection Bias

19 January 2022

Papers citing "Debiased Graph Neural Networks with Agnostic Label Selection Bias"

29 / 29 papers shown

Title
Causal invariant geographic network representations with feature and structural distribution shifts Yuhan Wang Silu He Qinyao Luo Hongyuan Yuan Ling Zhao Jiawei Zhu Haifeng Li OOD 64 0 0 25 Mar 2025
Contextual Representation Anchor Network to Alleviate Selection Bias in Few-Shot Drug Discovery Ruifeng Li Wei Liu Xiangxin Zhou Mingqian Li Qiang Zhang Hongyang Chen Xuemin Lin 44 0 0 28 Oct 2024
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification Xiaoxue Han Huzefa Rangwala Yue Ning BDL OOD CML 32 0 0 27 Oct 2024
Deep Graph Anomaly Detection: A Survey and New Perspectives Hezhe Qiao Hanghang Tong Bo An Irwin King Charu Aggarwal Guansong Pang 35 6 0 16 Sep 2024
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph Weihuang Zheng Jiashuo Liu Jiaxing Li Jiayun Wu Peng Cui Youyong Kong OOD 41 0 0 03 Jun 2024
IENE: Identifying and Extrapolating the Node Environment for Out-of-Distribution Generalization on Graphs Haoran Yang Xiaobing Pei Kai Yuan 27 0 0 02 Jun 2024
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization Donglin Xia Xiao Wang Nian Liu Chuan Shi 45 10 0 06 Mar 2024
Graph Fairness Learning under Distribution Shifts Yibo Li Xiao Wang Yujie Xing Shaohua Fan Ruijia Wang Yaoqi Liu Chuan Shi OOD 36 7 0 30 Jan 2024
Alleviating Structural Distribution Shift in Graph Anomaly Detection Yuan Gao Xiang Wang Xiangnan He Zhenguang Liu Huamin Feng Yongdong Zhang 15 62 0 25 Jan 2024
Graph Contrastive Invariant Learning from the Causal Perspective Yanhu Mo Xiao Wang Shaohua Fan Chuan Shi 32 14 0 23 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
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 38 6 0 10 Dec 2023
Causality and Independence Enhancement for Biased Node Classification Guoxin Chen Yongqing Wang Fangda Guo Qinglang Guo Jiangli Shao Huawei Shen Xueqi Cheng CML AI4CE OOD 37 14 0 14 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 27 19 0 08 Oct 2023
FRGNN: Mitigating the Impact of Distribution Shift on Graph Neural Networks via Test-Time Feature Reconstruction Ruitian Ding Jielong Yang Feng Ji Xionghu Zhong Linbo Xie 34 1 0 18 Aug 2023
Graph Out-of-Distribution Generalization with Controllable Data Augmentation Bin Lu Xiaoying Gan Ze Zhao Shiyu Liang Luoyi Fu Xinbing Wang Cheng Zhou 27 6 0 16 Aug 2023
Deep Stable Multi-Interest Learning for Out-of-distribution Sequential Recommendation Qiang Liu Zhaocheng Liu Zhen Zhu Shu Wu Liang Wang OOD OODD 40 3 0 12 Apr 2023
Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network Wendong Bi Bingbing Xu Xiaoqian Sun Li Xu Huawei Shen Xueqi Cheng 22 16 0 02 Feb 2023
Directed Acyclic Graph Structure Learning from Dynamic Graphs Shaohua Fan Shuyang Zhang Xiao Wang Chuan Shi CML 36 5 0 30 Nov 2022
Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure Shaohua Fan Xiao Wang Yanhu Mo Chuan Shi Jian Tang CML OOD AI4CE 36 89 0 28 Sep 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
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Wang Ziwei Zhang Wenwu Zhu OOD CML 21 96 0 16 Feb 2022
Stable Prediction on Graphs with Agnostic Distribution Shift Shengyu Zhang Kun Kuang J. Qiu Jin Yu Zhou Zhao Hongxia Yang Zhongfei Zhang Fei Wu OOD 39 8 0 08 Oct 2021
Does Invariant Risk Minimization Capture Invariance? Pritish Kamath Akilesh Tangella Danica J. Sutherland Nathan Srebro OOD 196 125 0 04 Jan 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 94 561 0 04 Jan 2021
Out-of-Distribution Generalization via Risk Extrapolation (REx) David M. Krueger Ethan Caballero J. Jacobsen Amy Zhang Jonathan Binas Dinghuai Zhang Rémi Le Priol Aaron Courville OOD 215 901 0 02 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 1,945 0 09 Jun 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 172 1,778 0 02 Mar 2017
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 251 1,811 0 25 Nov 2016