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Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift

5 November 2022

Qitian Wu

Xiang Wang

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Papers citing "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift"

25 / 25 papers shown

Title
Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics Zhichen Zeng Ruizhong Qiu Wenxuan Bao Tianxin Wei Xiao Lin Yuchen Yan Tarek Abdelzaher Jiawei Han Hanghang Tong OOD AI4CE 107 2 0 19 May 2025
Virtual Nodes Can Help: Tackling Distribution Shifts in Federated Graph Learning Xingbo Fu Zihan Chen Yinhan He Song Wang Binchi Zhang Chen Chen Jundong Li OOD FedML 191 1 0 24 Feb 2025
Unleashing the Power of Large Language Model for Denoising Recommendation Shuyao Wang Zhi Zheng Yongduo Sui Hui Xiong 185 0 0 13 Feb 2025
Towards Pattern-aware Data Augmentation for Temporal Knowledge Graph Completion Jiasheng Zhang Deqiang Ouyang Shuang Liang Jie Shao 88 0 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 147 4 0 31 Dec 2024
NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Language Yuanyuan Liang Tingyu Xie Gan Peng Zihao Huang Yunshi Lan Weining Qian LLMAG 117 1 0 11 Dec 2024
Scale Invariance of Graph Neural Networks Qin Jiang Chengjia Wang Michael Lones Wei Pang GNN 170 0 0 28 Nov 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 Li Jundong Li Kaize Ding OOD 150 5 0 25 Oct 2024
Mitigating Graph Covariate Shift via Score-based Out-of-distribution Augmentation Bohan Wang Yurui Chang Lu Lin OODD OOD 99 0 0 23 Oct 2024
Control the GNN: Utilizing Neural Controller with Lyapunov Stability for Test-Time Feature Reconstruction Jielong Yang Rui Ding Feng Ji Hongbin Wang Linbo Xie 147 0 0 13 Oct 2024
Exploring Empty Spaces: Human-in-the-Loop Data Augmentation Catherine Yeh Donghao Ren Yannick Assogba Dominik Moritz Fred Hohman 89 0 0 01 Oct 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 144 2 0 03 Aug 2024
Data Augmentation in Graph Neural Networks: The Role of Generated Synthetic Graphs Sumeyye Bas Kıymet Kaya Resul Tugay Ş. Öğüdücü 43 0 0 20 Jul 2024
Improving Graph Out-of-distribution Generalization Beyond Causality Can Xu Yao Cheng Jianxiang Yu Haosen Wang Jingsong Lv Yao Liu Xiang Li OOD 160 0 0 14 Jul 2024
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph Weihuang Zheng Jiashuo Liu Jiaxing Li Jiayun Wu Peng Cui Youyong Kong OOD 78 1 0 03 Jun 2024
Harnessing the Power of Vicinity-Informed Analysis for Classification under Covariate Shift Mitsuhiro Fujikawa Yohei Akimoto Jun Sakuma Kazuto Fukuchi 48 0 0 27 May 2024
A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges Wei Ju Siyu Yi Yifan Wang Zhiping Xiao Zhengyan Mao ... Senzhang Wang Xinwang Liu Xiao Luo Philip S. Yu Ming Zhang AI4CE 134 39 0 07 Mar 2024
Pairwise Alignment Improves Graph Domain Adaptation Shikun Liu Deyu Zou Han Zhao Pan Li OOD 116 9 0 02 Mar 2024
Graph Learning under Distribution Shifts: A Comprehensive Survey on Domain Adaptation, Out-of-distribution, and Continual Learning Man Wu Xin-Yang Zheng Qin Zhang Xiao Shen Xiong Luo Xingquan Zhu Shirui Pan OOD 151 12 0 26 Feb 2024
Dynamic Sparse Learning: A Novel Paradigm for Efficient Recommendation Shuyao Wang Yongduo Sui Jiancan Wu Zhi Zheng Hui Xiong 56 16 0 05 Feb 2024
EXGC: Bridging Efficiency and Explainability in Graph Condensation Sihang Li Xinglin Li Yongduo Sui Yuan Gao Guibin Zhang Kun Wang Xiang Wang Xiangnan He DD 114 21 0 05 Feb 2024
Future Directions in the Theory of Graph Machine Learning Christopher Morris Fabrizio Frasca Nadav Dym Haggai Maron .Ismail .Ilkan Ceylan Ron Levie Derek Lim Michael M. Bronstein Martin Grohe Stefanie Jegelka AI4CE 125 7 0 03 Feb 2024
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts Shirley Wu Kaidi Cao Bruno Ribeiro James Zou J. Leskovec OOD 73 3 0 07 Dec 2023
Exploring Causal Learning through Graph Neural Networks: An In-depth Review Simi Job Xiaohui Tao Taotao Cai Haoran Xie Lin Li Jianming Yong Qing Li CML AI4CE 81 5 0 25 Nov 2023
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 125 102 0 16 Feb 2022