Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution
Generalization

Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization

18 December 2023

Cheng Yang

Papers citing "Graph Invariant Learning with Subgraph Co-mixup for Out-Of-Distribution Generalization"

18 / 18 papers shown

Title
Soft causal learning for generalized molecule property prediction: An environment perspective Limin Li Kuo Yang Wenjie Du Pengkun Wang Zhengyang Zhou Yang Wang OOD AI4CE 36 0 0 07 May 2025
Towards Invariance to Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 48 1 0 20 Feb 2025
BrainOOD: Out-of-distribution Generalizable Brain Network Analysis Jiaxing Xu Yongqiang Chen Xia Dong Mengcheng Lan Tiancheng Huang Qingtian Bian James Cheng Yiping Ke OOD 57 0 0 02 Feb 2025
On the Utilization of Unique Node Identifiers in Graph Neural Networks Maya Bechler-Speicher Moshe Eliasof Carola-Bibiane Schönlieb Ran Gilad-Bachrach Amir Globerson 23 0 0 04 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 R. Li Jundong Li Kaize Ding OOD 45 2 0 25 Oct 2024
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization Xin Sun Liang Wang Qiang Liu Shu Wu Zilei Wang Liang Wang OOD CML 28 5 0 08 Aug 2024
Improving Graph Out-of-distribution Generalization on Real-world Data Can Xu Yao Cheng Jianxiang Yu Haosen Wang Jingsong Lv Xiang Li OOD 21 0 0 14 Jul 2024
Teleporter Theory: A General and Simple Approach for Modeling Cross-World Counterfactual Causality Jiangmeng Li Bin Qin Qirui Ji Yi Li Wenwen Qiang Jianwen Cao Fanjiang Xu 36 0 0 17 Jun 2024
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization Donglin Xia Xiao Wang Nian Liu Chuan Shi 32 3 0 06 Mar 2024
Pairwise Alignment Improves Graph Domain Adaptation Shikun Liu Deyu Zou Han Zhao Pan Li OOD 21 7 0 02 Mar 2024
Data Augmentation on Graphs: A Technical Survey Jiajun Zhou Chenxuan Xie Shengbo Gong Z. Wen Xiangyu Zhao Qi Xuan Xiaoniu Yang AI4TS 11 8 0 20 Dec 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 89 170 0 30 Jan 2022
DrugOOD: Out-of-Distribution (OOD) Dataset Curator and Benchmark for AI-aided Drug Discovery -- A Focus on Affinity Prediction Problems with Noise Annotations Yuanfeng Ji Lu Zhang Jiaxiang Wu Bing Wu Long-Kai Huang ... Ping Luo Shuigeng Zhou Junzhou Huang Peilin Zhao Yatao Bian OOD 54 73 0 24 Jan 2022
Graph Transplant: Node Saliency-Guided Graph Mixup with Local Structure Preservation Joonhyung Park Hajin Shim Eunho Yang 79 48 0 10 Nov 2021
Co-Mixup: Saliency Guided Joint Mixup with Supermodular Diversity Jang-Hyun Kim Wonho Choo Hosan Jeong Hyun Oh Song 195 173 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 159 463 0 31 Dec 2020
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 128 112 0 17 Oct 2020
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 215 888 0 02 Mar 2020