OOD-GNN: Out-of-Distribution Generalized Graph Neural Network

7 December 2021

Papers citing "OOD-GNN: Out-of-Distribution Generalized Graph Neural Network"

24 / 24 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 46 0 0 07 May 2025
Federated Causal Inference in Healthcare: Methods, Challenges, and Applications Haoyang Li Jie Xu Kyra Gan Fei Wang Chengxi Zang FedML CML 31 0 0 04 May 2025
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation Danny Wang Ruihong Qiu Guangdong Bai Zi Huang 63 0 0 09 Feb 2025
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
Learning to Model Graph Structural Information on MLPs via Graph Structure Self-Contrasting Lirong Wu Haitao Lin Guojiang Zhao Cheng Tan Stan Z. Li 16 0 0 09 Sep 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
Unifying Invariant and Variant Features for Graph Out-of-Distribution via Probability of Necessity and Sufficiency Xuexin Chen Ruichu Cai Kaitao Zheng Zhifan Jiang Zhengting Huang Zhifeng Hao Zijian Li 44 0 0 21 Jul 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 34 36 0 07 Mar 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
Identifying Semantic Component for Robust Molecular Property Prediction Zijian Li Zunhong Xu Ruichu Cai Zhenhui Yang Yuguang Yan Zhifeng Hao Guan-Hong Chen Kun Zhang 18 9 0 08 Nov 2023
SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection Zhihao Ding Jieming Shi Shiqi Shen Xuequn Shang Jiannong Cao Zhipeng Wang Zhi Gong OODD OOD 27 4 0 16 Oct 2023
Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization Ling Yang Jiayi Zheng Heyuan Wang Zhongyi Liu Zhilin Huang Shenda Hong Wentao Zhang Bin Cui 14 13 0 28 Jun 2023
A Comprehensive Survey on Deep Graph Representation Learning Wei Ju Zheng Fang Yiyang Gu Zequn Liu Qingqing Long ... Jingyang Yuan Yusheng Zhao Yifan Wang Xiao Luo Ming Zhang GNN AI4TS 25 141 0 11 Apr 2023
Curriculum Graph Machine Learning: A Survey Haoyang Li Xin Eric Wang Wenwu Zhu 15 16 0 06 Feb 2023
Predicting the Silent Majority on Graphs: Knowledge Transferable Graph Neural Network Wendong Bi Bingbing Xu Xiaoqian Sun Li Xu Huawei Shen Xueqi Cheng 15 16 0 02 Feb 2023
BeGin: Extensive Benchmark Scenarios and An Easy-to-use Framework for Graph Continual Learning Jihoon Ko Shinhwan Kang Taehyung Kwon Heechan Moon Kijung Shin CLL 21 7 0 26 Nov 2022
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 19 77 0 21 Nov 2022
Graph Contrastive Learning with Personalized Augmentation X. Zhang Qiaoyu Tan Xiao Shi Huang Bo-wen Li 28 15 0 14 Sep 2022
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 22 115 0 16 Jun 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
Revealing the Distributional Vulnerability of Discriminators by Implicit Generators Zhilin Zhao LongBing Cao Kun-Yu Lin 16 11 0 23 Aug 2021
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 139 123 0 17 Oct 2020
Learning to Decompose and Disentangle Representations for Video Prediction Jun-Ting Hsieh Bingbin Liu De-An Huang Li Fei-Fei Juan Carlos Niebles DRL 127 304 0 11 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 159 1,766 0 02 Mar 2017