GOOD: A Graph Out-of-Distribution Benchmark

16 June 2022

Papers citing "GOOD: A Graph Out-of-Distribution Benchmark"

46 / 96 papers shown

Title
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
GraphMETRO: Mitigating Complex Graph Distribution Shifts via Mixture of Aligned Experts Shirley Wu Kaidi Cao Bruno Ribeiro James Y. Zou J. Leskovec OOD 9 3 0 07 Dec 2023
Environment-Aware Dynamic Graph Learning for Out-of-Distribution Generalization Haonan Yuan Qingyun Sun Xingcheng Fu Ziwei Zhang Cheng Ji Hao Peng Jianxin Li OOD 22 15 0 18 Nov 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 15 9 0 08 Nov 2023
HKTGNN: Hierarchical Knowledge Transferable Graph Neural Network-based Supply Chain Risk Assessment Zhanting Zhou Kejun Bi Yuyanzhen Zhong Chao Tang Dongfen Li Shi Ying Ruijin Wang 13 0 0 07 Nov 2023
Does Invariant Graph Learning via Environment Augmentation Learn Invariance? Yongqiang Chen Yatao Bian Kaiwen Zhou Binghui Xie Bo Han James Cheng OOD 14 33 0 29 Oct 2023
Towards Combinatorial Generalization for Catalysts: A Kohn-Sham Charge-Density Approach Phillip Pope David Jacobs 9 3 0 28 Oct 2023
Learning Invariant Molecular Representation in Latent Discrete Space Zhuang Xiang Qiang Zhang Keyan Ding Yatao Bian Xiao Wang Jingsong Lv Hongyang Chen Huajun Chen OOD 26 16 0 22 Oct 2023
Conformal Drug Property Prediction with Density Estimation under Covariate Shift Siddhartha Laghuvarapu Zhen Lin Jimeng Sun 12 4 0 18 Oct 2023
ADMEOOD: Out-of-Distribution Benchmark for Drug Property Prediction Shuoying Wei Xinlong Wen Lida Zhu Songquan Li Rongbo Zhu OOD 17 1 0 11 Oct 2023
Lo-Hi: Practical ML Drug Discovery Benchmark Simon Steshin VLM 13 7 0 10 Oct 2023
Towards out-of-distribution generalizable predictions of chemical kinetics properties Zihao W. Wang Yongqiang Chen Yang Duan Weijiang Li Bo Han James Cheng Hanghang Tong OOD 26 6 0 04 Oct 2023
Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective Haoliang Wang Chen Zhao Yunhui Guo Kai Jiang Feng Chen 20 1 0 18 Sep 2023
Bridged-GNN: Knowledge Bridge Learning for Effective Knowledge Transfer Wendong Bi Xueqi Cheng Bingbing Xu Xiaoqian Sun Li Xu Huawei Shen 25 10 0 18 Aug 2023
Graph Relation Aware Continual Learning Q. Shen Weijieying Ren Wei Qin CLL BDL 11 2 0 16 Aug 2023
MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning Yun Zhu Haizhou Shi Zhenshuo Zhang Siliang Tang 13 7 0 24 Jul 2023
OpenGDA: Graph Domain Adaptation Benchmark for Cross-network Learning Boshen Shi Yongqing Wang Fangda Guo Jiangli Shao Huawei Shen Xueqi Cheng OOD AI4CE 23 3 0 21 Jul 2023
Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs Zhikai Chen Haitao Mao Hang Li Wei Jin Haifang Wen ... Shuaiqiang Wang Dawei Yin Wenqi Fan Hui Liu Jiliang Tang AI4CE 25 261 0 07 Jul 2023
Bkd-FedGNN: A Benchmark for Classification Backdoor Attacks on Federated Graph Neural Network F. Liu Siqi Lai Yansong NING Hao Liu AAML FedML 14 3 0 17 Jun 2023
Graph Structure and Feature Extrapolation for Out-of-Distribution Generalization Xiner Li Shurui Gui Youzhi Luo Shuiwang Ji OODD OOD 10 11 0 13 Jun 2023
Explaining and Adapting Graph Conditional Shift Qi Zhu Yizhu Jiao Natalia Ponomareva Jiawei Han Bryan Perozzi OOD 8 10 0 05 Jun 2023
Structural Re-weighting Improves Graph Domain Adaptation Shikun Liu Tianchun Li Yongbin Feng Nhan Tran H. Zhao Qiu Qiang Pan Li OOD AI4CE 11 30 0 05 Jun 2023
Do-GOOD: Towards Distribution Shift Evaluation for Pre-Trained Visual Document Understanding Models Jiabang He Yilang Hu Lei Wang Xingdong Xu Ning Liu Hui-juan Liu Hengtao Shen VLM OOD 17 2 0 05 Jun 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? Haitao Mao Zhikai Chen Wei Jin Haoyu Han Yao Ma Tong Zhao Neil Shah Jiliang Tang 21 31 0 02 Jun 2023
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization Shurui Gui Meng Liu Xiner Li Youzhi Luo Shuiwang Ji CML OOD 8 14 0 01 Jun 2023
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts Gleb Bazhenov Denis Kuznedelev A. Malinin Artem Babenko Liudmila Prokhorenkova OOD 6 3 0 27 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
State of the Art and Potentialities of Graph-level Learning Zhenyu Yang Ge Zhang Jia Wu Jian Yang Quan.Z Sheng ... Charu C. Aggarwal Hao Peng Wenbin Hu Edwin R. Hancock Pietro Lio' GNN AI4CE 30 10 0 14 Jan 2023
GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective Linyi Yang Shuibai Zhang Libo Qin Yafu Li Yidong Wang Hanmeng Liu Jindong Wang Xingxu Xie Yue Zhang ELM 17 79 0 15 Nov 2022
Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift Yongduo Sui Qitian Wu Jiancan Wu Qing Cui Longfei Li An Zhang Xiang Wang Xiangnan He OOD 17 31 0 05 Nov 2022
Empowering Graph Representation Learning with Test-Time Graph Transformation Wei Jin Tong Zhao Jiayu Ding Yozen Liu Jiliang Tang Neil Shah OOD 84 59 0 07 Oct 2022
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks Hyungeun Lee Kijung Yoon AI4CE 15 2 0 14 Sep 2022
Learning Hierarchical Protein Representations via Complete 3D Graph Networks Limei Wang Haoran Liu Yi Liu Jerry Kurtin Shuiwang Ji GNN 10 54 0 26 Jul 2022
FlowX: Towards Explainable Graph Neural Networks via Message Flows Shurui Gui Hao Yuan Jie Wang Qicheng Lao Kang Li Shuiwang Ji 22 11 0 26 Jun 2022
Evaluating Self-Supervised Learning for Molecular Graph Embeddings Hanchen Wang Jean Kaddour Shengchao Liu Jian Tang Joan Lasenby Qi Liu 14 20 0 16 Jun 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 70 37 0 30 May 2022
AUC Maximization in the Era of Big Data and AI: A Survey Tianbao Yang Yiming Ying 8 178 0 28 Mar 2022
Graph Data Augmentation for Graph Machine Learning: A Survey Tong Zhao Wei Jin Yozen Liu Yingheng Wang Gang Liu Stephan Günnemann Neil Shah Meng-Long Jiang OOD 12 78 0 17 Feb 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 8 96 0 16 Feb 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 89 222 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
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 159 589 0 31 Dec 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
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 208 1,329 0 12 Feb 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 154 1,748 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 234 1,801 0 25 Nov 2016