GOOD: A Graph Out-of-Distribution Benchmark

16 June 2022

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

50 / 96 papers shown

Title
InfoNCE is a Free Lunch for Semantically guided Graph Contrastive Learning Zixu Wang Bingbing Xu Yige Yuan Huawei Shen Xueqi Cheng 21 0 0 07 May 2025
Adversarial Cooperative Rationalization: The Risk of Spurious Correlations in Even Clean Datasets W. Liu Zhongyu Niu Lang Gao Zhiying Deng Jun Wang H. Wang Ruixuan Li 48 1 0 04 May 2025
Causal invariant geographic network representations with feature and structural distribution shifts Yuhan Wang Silu He Qinyao Luo Hongyuan Yuan Ling Zhao Jiawei Zhu Haifeng Li OOD 56 0 0 25 Mar 2025
Out-of-Distribution Generalization on Graphs via Progressive Inference Yiming Xu Bin Shi Zhen Peng Huixiang Liu Bo Dong Chen Chen OOD AI4CE 71 0 0 04 Mar 2025
Structural Alignment Improves Graph Test-Time Adaptation Hans Hao-Hsun Hsu Shikun Liu Han Zhao Pan Li OOD TTA 55 0 0 25 Feb 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 59 1 0 24 Feb 2025
DivIL: Unveiling and Addressing Over-Invariance for Out-of- Distribution Generalization Jiaqi Wang Yuhang Zhou Zhixiong Zhang Qiguang Chen Yongqiang Chen James Cheng OODD 53 1 0 18 Feb 2025
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs Song Wang Zhen Tan Yaochen Zhu Chuxu Zhang Jundong Li OOD 93 0 0 11 Feb 2025
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation Danny Wang Ruihong Qiu Guangdong Bai Zi Huang 53 0 0 09 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 60 0 0 02 Feb 2025
A Unified Invariant Learning Framework for Graph Classification Yongduo Sui Jie Sun Shuyao Wang Zemin Liu Qing Cui Longfei Li Xiang Wang OOD 78 2 0 22 Jan 2025
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution Generalization Song Wang Xiaodong Yang Rashidul Islam Huiyuan Chen Minghua Xu Jundong Li Yiwei Cai OODD 52 2 0 07 Jan 2025
Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting Hongjun Wang Jiyuan Chen Lingyu Zhang Renhe Jiang Xuan Song AI4TS 68 0 0 18 Nov 2024
DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification Xiaoxue Han Huzefa Rangwala Yue Ning BDL OOD CML 25 0 0 27 Oct 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
GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models Zhixia He Chen Zhao Minglai Shao Yujie Lin Dong Li Q. Tian DiffM 20 4 0 23 Oct 2024
Mitigating Graph Covariate Shift via Score-based Out-of-distribution Augmentation Bohan Wang Yurui Chang Lu Lin OODD OOD 27 0 0 23 Oct 2024
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution Shifts Jinluan Yang Zhengyu Chen Teng Xiao Wenqiao Zhang Yong Lin Kun Kuang 48 0 0 18 Aug 2024
DIVE: Subgraph Disagreement for Graph Out-of-Distribution Generalization Xin Sun Liang Wang Qiang Liu Shu Wu Zilei Wang Liang Wang OOD CML 31 5 0 08 Aug 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 35 3 0 03 Aug 2024
Can Modifying Data Address Graph Domain Adaptation? Renhong Huang Jiarong Xu Xin Jiang Ruichuan An Yang Yang OOD 39 6 0 27 Jul 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 36 0 0 21 Jul 2024
Improving Graph Out-of-distribution Generalization on Real-world Data Can Xu Yao Cheng Jianxiang Yu Haosen Wang Jingsong Lv Xiang Li OOD 29 0 0 14 Jul 2024
Unifying Unsupervised Graph-Level Anomaly Detection and Out-of-Distribution Detection: A Benchmark Yili Wang Yixin Liu Xu Shen Chenyu Li Kaize Ding Rui Miao Ying Wang Shirui Pan Xin Wang 29 6 0 21 Jun 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 39 0 0 17 Jun 2024
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling Tianxiang Zhao Dongsheng Luo Xiang Zhang Suhang Wang 18 3 0 14 Jun 2024
A Comprehensive Graph Pooling Benchmark: Effectiveness, Robustness and Generalizability Pengyun Wang Junyu Luo Yanxin Shen Siyu Heng Xiao Luo 39 1 0 13 Jun 2024
How Interpretable Are Interpretable Graph Neural Networks? Yongqiang Chen Yatao Bian Bo Han James Cheng 39 4 0 12 Jun 2024
Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency Yuchao Lin Jacob Helwig Shurui Gui Shuiwang Ji 29 7 0 11 Jun 2024
Topology-Aware Dynamic Reweighting for Distribution Shifts on Graph Weihuang Zheng Jiashuo Liu Jiaxing Li Jiayun Wu Peng Cui Youyong Kong OOD 35 0 0 03 Jun 2024
Negative as Positive: Enhancing Out-of-distribution Generalization for Graph Contrastive Learning Zixu Wang Bingbing Xu Yige Yuan Huawei Shen Xueqi Cheng OODD 23 2 0 25 May 2024
Adapting Multi-modal Large Language Model to Concept Drift From Pre-training Onwards Xiaoyu Yang Jie Lu Enshui Yu VLM 23 1 0 22 May 2024
Safety in Graph Machine Learning: Threats and Safeguards Song Wang Yushun Dong Binchi Zhang Zihan Chen Xingbo Fu Yinhan He Cong Shen Chuxu Zhang Nitesh V. Chawla Jundong Li 37 7 0 17 May 2024
Harnessing Collective Structure Knowledge in Data Augmentation for Graph Neural Networks Rongrong Ma Guansong Pang Ling-Hao Chen AI4CE 27 0 0 17 May 2024
Optimizing OOD Detection in Molecular Graphs: A Novel Approach with Diffusion Models Xu Shen Yili Wang Kaixiong Zhou Shirui Pan Xin Wang 27 3 0 24 Apr 2024
Graph Machine Learning in the Era of Large Language Models (LLMs) Wenqi Fan Shijie Wang Jiani Huang Zhikai Chen Yu Song ... Haitao Mao Hui Liu Xiaorui Liu Dawei Yin Qing Li AI4CE 24 21 0 23 Apr 2024
Test-Time Training on Graphs with Large Language Models (LLMs) Jiaxin Zhang Yiqi Wang Xihong Yang Siwei Wang Yu Feng Yu Shi Ruicaho Ren En Zhu Xinwang Liu 40 2 0 21 Apr 2024
Active Test-Time Adaptation: Theoretical Analyses and An Algorithm Shurui Gui Xiner Li Shuiwang Ji TTA 59 10 0 07 Apr 2024
Uncertainty in Graph Neural Networks: A Survey Fangxin Wang Yuqing Liu Kay Liu Yibo Wang Sourav Medya Philip S. Yu AI4CE 40 8 0 11 Mar 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
Learning Invariant Representations of Graph Neural Networks via Cluster Generalization Donglin Xia Xiao Wang Nian Liu Chuan Shi 35 3 0 06 Mar 2024
Improving out-of-distribution generalization in graphs via hierarchical semantic environments Yinhua Piao Sangseon Lee Yijingxiu Lu Sun Kim OOD 26 2 0 04 Mar 2024
OpenGraph: Towards Open Graph Foundation Models Lianghao Xia Ben Kao Chao Huang AI4CE 27 33 0 02 Mar 2024
Unifying Invariance and Spuriousity 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 13 2 0 14 Feb 2024
Subgraph Pooling: Tackling Negative Transfer on Graphs Zehong Wang Zheyuan Zhang Chuxu Zhang Yanfang Ye 28 6 0 14 Feb 2024
Investigating Out-of-Distribution Generalization of GNNs: An Architecture Perspective Kai Guo Hongzhi Wen Wei Jin Yaming Guo Jiliang Tang Yi Chang OOD AI4CE 11 3 0 13 Feb 2024
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study Sadman Sadeed Omee Nihang Fu Rongzhi Dong Ming Hu Jianjun Hu OOD 21 17 0 16 Jan 2024
GOODAT: Towards Test-time Graph Out-of-Distribution Detection Luzhi Wang Dongxiao He He Zhang Yixin Liu Wenjie Wang Shirui Pan Di Jin Tat-Seng Chua OODD OOD 18 10 0 10 Jan 2024
Few-Shot Causal Representation Learning for Out-of-Distribution Generalization on Heterogeneous Graphs Pengfei Ding Yan Wang Guanfeng Liu Nan Wang Xiaofang Zhou OODD OOD 18 2 0 07 Jan 2024
Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks Puja Trivedi Mark Heimann Rushil Anirudh Danai Koutra Jayaraman J. Thiagarajan UQCV 21 4 0 07 Jan 2024