Exploring Edge Disentanglement for Node Classification

23 February 2022

Papers citing "Exploring Edge Disentanglement for Node Classification"

24 / 24 papers shown

Title
Contrastive Graph Representation Learning with Adversarial Cross-view Reconstruction and Information Bottleneck Yuntao Shou Haozhi Lan Xiangyong Cao 38 11 0 01 Aug 2024
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang 26 3 0 14 Jun 2024
Disentangled Hyperbolic Representation Learning for Heterogeneous Graphs Qijie Bai Changli Nie Haiwei Zhang Zhicheng Dou Xiaojie Yuan 43 0 0 14 Jun 2024
Fair Graph Representation Learning via Sensitive Attribute Disentanglement Yuchang Zhu Jintang Li Zibin Zheng Liang Chen 21 2 0 11 May 2024
Disambiguated Node Classification with Graph Neural Networks Tianxiang Zhao Xiang Zhang Suhang Wang AI4CE 29 2 0 13 Feb 2024
EsaCL: Efficient Continual Learning of Sparse Models Weijieying Ren V. Honavar CLL 22 3 0 11 Jan 2024
Graph Relation Aware Continual Learning Q. Shen Weijieying Ren Wei Qin CLL BDL 18 2 0 16 Aug 2023
Learning Disentangled Representations in Signed Directed Graphs without Social Assumptions Geonwoo Ko Jinhong Jung 20 2 0 06 Jul 2023
Contrastive Disentangled Learning on Graph for Node Classification Xiaojuan Zhang Jun Fu Shuang Li SSL 18 1 0 20 Jun 2023
Variational Disentangled Graph Auto-Encoders for Link Prediction Jun Fu Xiaojuan Zhang Shuang Li Dali Chen CML DRL 22 3 0 20 Jun 2023
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations Tianxiang Zhao Wenchao Yu Suhang Wang Lucy Wang Xiang Zhang Yuncong Chen Yanchi Liu Wei Cheng Haifeng Chen 22 8 0 13 Jun 2023
Self-Explainable Graph Neural Networks for Link Prediction Huaisheng Zhu Dongsheng Luo Xianfeng Tang Junjie Xu Hui Liu Suhang Wang 16 1 0 21 May 2023
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang 26 7 0 07 Jan 2023
TopoImb: Toward Topology-level Imbalance in Learning from Graphs Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang AI4CE 30 11 0 16 Dec 2022
DyTed: Disentangled Representation Learning for Discrete-time Dynamic Graph Kaike Zhang Qi Cao Gaolin Fang Bingbing Xu Hongjian Zou Huawei Shen Xueqi Cheng 16 19 0 19 Oct 2022
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning Shijie Zhou Zhimeng Guo Charu C. Aggarwal Xiang Zhang Suhang Wang 28 15 0 03 Aug 2022
Decoupled Self-supervised Learning for Non-Homophilous Graphs Teng Xiao Zhengyu Chen Zhimeng Guo Zeyang Zhuang Suhang Wang BDL SSL 23 18 0 07 Jun 2022
Towards Faithful and Consistent Explanations for Graph Neural Networks Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang FAtt 52 18 0 27 May 2022
ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting Jingwei Guo Kaizhu Huang Rui Zhang Xinping Yi AAML 28 4 0 27 May 2022
Semi-supervised Drifted Stream Learning with Short Lookback Wei-Ya Ren Pengyang Wang Xiaolin Li C. Hughes Yanjie Fu AI4TS 26 15 0 25 May 2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability Enyan Dai Tianxiang Zhao Huaisheng Zhu Jun Xu Zhimeng Guo Hui Liu Jiliang Tang Suhang Wang 29 132 0 18 Apr 2022
Label-Wise Graph Convolutional Network for Heterophilic Graphs Enyan Dai Shijie Zhou Zhimeng Guo Suhang Wang 45 18 0 15 Oct 2021
Adversarial Graph Disentanglement Shuai Zheng Zhenfeng Zhu Zhizhe Liu Shuiwang Ji Yao Zhao 27 10 0 12 Mar 2021
Geom-GCN: Geometric Graph Convolutional Networks Hongbin Pei Bingzhen Wei Kevin Chen-Chuan Chang Yu Lei Bo Yang GNN 169 1,078 0 13 Feb 2020