Does Invariant Graph Learning via Environment Augmentation Learn Invariance?

Neural Information Processing Systems (NeurIPS), 2023

29 October 2023

Bo Han

Papers citing "Does Invariant Graph Learning via Environment Augmentation Learn Invariance?"

28 / 28 papers shown

Title
Quantifying Distributional Invariance in Causal Subgraph for IRM-Free Graph Generalization Yang Qiu Yixiong Zou Jun Wang Wei Liu Xiangyu Fu R. Li OOD 121 1 0 23 Oct 2025
Invariant Graph Transformer for Out-of-Distribution Generalization Tianyin Liao Ziwei Zhang Yufei Sun Chunyu Hu Jianxin Li OOD 122 1 0 01 Aug 2025
Out-of-Distribution Graph Models Merging Yidi Wang Jiawei Gu pei Xiaobing Xubin Zheng Xiao Luo Pengyang Wang Ziyue Qiao MoMe OODD 296 0 0 04 Jun 2025
Data Heterogeneity Modeling for Trustworthy Machine Learning Tianyu Wang Peng Cui 205 1 0 01 Jun 2025
Learning Repetition-Invariant Representations for Polymer Informatics Yihan Zhu Gang Liu Eric Inae Tengfei Luo Meng Jiang 264 0 0 15 May 2025
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 187 1 0 07 May 2025
Out-of-Distribution Generalization on Graphs via Progressive InferenceAAAI Conference on Artificial Intelligence (AAAI), 2025 Yiming Xu Bin Shi Zhen Peng Huixiang Liu Bo Dong Chen Chen OOD AI4CE 294 0 0 04 Mar 2025
Generative Risk Minimization for Out-of-Distribution Generalization on Graphs Song Wang Zhen Tan Yaochen Zhu Chuxu Zhang Wenlin Yao OOD 349 0 0 11 Feb 2025
BrainOOD: Out-of-distribution Generalizable Brain Network AnalysisInternational Conference on Learning Representations (ICLR), 2025 Jiaxing Xu Yongqiang Chen Xia Dong Mengcheng Lan Tiancheng Huang Qingtian Bian James Cheng Yiping Ke OOD 367 5 0 02 Feb 2025
Enhancing Distribution and Label Consistency for Graph Out-of-Distribution GeneralizationIndustrial Conference on Data Mining (IDM), 2024 Song Wang Xiaodong Yang Rashidul Islam Huiyuan Chen Minghua Xu Jundong Li Yiwei Cai OODD 379 4 0 07 Jan 2025
Scale Invariance of Graph Neural Networks Qin Jiang Chengjia Wang Michael Lones Wei Pang GNN 302 0 0 28 Nov 2024
Subgraph Aggregation for Out-of-Distribution Generalization on GraphsAAAI Conference on Artificial Intelligence (AAAI), 2024 Bowen Liu Haoyang Li Shuning Wang Shuo Nie Shanghang Zhang OODD CML 257 1 0 29 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 Li Jundong Li Kaize Ding OOD 321 9 0 25 Oct 2024
Score-based Conditional Out-of-Distribution Augmentation for Graph Covariate Shift Bohan Wang Yurui Chang Lu Lin Lu Lin OODD OOD 310 0 0 23 Oct 2024
Leveraging Invariant Principle for Heterophilic Graph Structure Distribution ShiftsThe Web Conference (WWW), 2024 Jinluan Yang Ruihao Zhang Teng Xiao Wenqiao Zhang Yong Lin Kun Kuang 389 7 0 18 Aug 2024
Invariant Graph Learning Meets Information Bottleneck for Out-of-Distribution Generalization Wenyu Mao Jiancan Wu Haoyang Liu Yongduo Sui Xiang Wang OOD 361 5 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 265 0 0 21 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 386 0 0 14 Jul 2024
Empowering Graph Invariance Learning with Deep Spurious Infomax Tianjun Yao Yongqiang Chen Zhenhao Chen Kai Hu Zhiqiang Shen Kun Zhang OOD 226 15 0 13 Jul 2024
How Interpretable Are Interpretable Graph Neural Networks? Yongqiang Chen Yatao Bian Bo Han James Cheng 178 13 0 12 Jun 2024
Improving out-of-distribution generalization in graphs via hierarchical semantic environments Yinhua Piao Sangseon Lee Yijingxiu Lu Sun Kim OOD 221 6 0 04 Mar 2024
Pairwise Alignment Improves Graph Domain Adaptation Shikun Liu Deyu Zou Han Zhao Pan Li OOD 328 20 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 159 2 0 14 Feb 2024
Enhancing Evolving Domain Generalization through Dynamic Latent RepresentationsAAAI Conference on Artificial Intelligence (AAAI), 2024 Binghui Xie Yongqiang Chen Jiaqi Wang Kaiwen Zhou Bo Han Wei Meng James Cheng 221 8 0 16 Jan 2024
When Graph Neural Network Meets Causality: Opportunities, Methodologies and An Outlook Wenzhao Jiang Hao Liu Hui Xiong CML AI4CE 439 9 0 19 Dec 2023
Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication ChannelInternational Conference on Learning Representations (ICLR), 2023 Xuan Li Zhanke Zhou Jiangchao Yao Yu Rong Jun Liu Bo Han 258 11 0 02 Nov 2023
Discovering environments with XRMInternational Conference on Machine Learning (ICML), 2023 Mohammad Pezeshki Diane Bouchacourt Mark Ibrahim Jimuyang Zhang Pascal Vincent David Lopez-Paz 194 21 0 28 Sep 2023
Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution GeneralizationNeural Information Processing Systems (NeurIPS), 2023 Shurui Gui Meng Liu Xiner Li Youzhi Luo Shuiwang Ji CML OOD 501 41 0 01 Jun 2023