Timezone: »
Despite recent success in using the invariance principle for out-of-distribution (OOD) generalization on Euclidean data (e.g., images), studies on graph data are still limited. Different from images, the complex nature of graphs poses unique challenges to adopting the invariance principle. In particular, distribution shifts on graphs can appear in a variety of forms such as attributes and structures, making it difficult to identify the invariance. Moreover, domain or environment partitions, which are often required by OOD methods on Euclidean data, could be highly expensive to obtain for graphs. To bridge this gap, we propose a new framework, called Causality Inspired Invariant Graph LeArning (CIGA), to capture the invariance of graphs for guaranteed OOD generalization under various distribution shifts. Specifically, we characterize potential distribution shifts on graphs with causal models, concluding that OOD generalization on graphs is achievable when models focus only on subgraphs containing the most information about the causes of labels. Accordingly, we propose an information-theoretic objective to extract the desired subgraphs that maximally preserve the invariant intra-class information. Learning with these subgraphs is immune to distribution shifts. Extensive experiments on 16 synthetic or real-world datasets, including a challenging setting -- DrugOOD, from AI-aided drug discovery, validate the superior OOD performance of CIGA.
Author Information
Yongqiang Chen (The Chinese University of Hong Kong)
Yonggang Zhang (Hong Kong Baptist University)
Yatao Bian (Tencent AI Lab)
Han Yang (Department of Computer Science and Engineering, The Chinese University of Hong Kong)
MA Kaili (CUHK)
Binghui Xie (Fudan University)
Tongliang Liu (The University of Sydney)
Bo Han (HKBU / RIKEN)
James Cheng (The Chinese University of Hong Kong)
More from the Same Authors
-
2021 Spotlight: TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation »
Haoang Chi · Feng Liu · Wenjing Yang · Long Lan · Tongliang Liu · Bo Han · William Cheung · James Kwok -
2022 Poster: RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning »
Yingbin Bai · Erkun Yang · Zhaoqing Wang · Yuxuan Du · Bo Han · Cheng Deng · Dadong Wang · Tongliang Liu -
2022 Poster: Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks »
Jianan Zhou · Jianing Zhu · Jingfeng ZHANG · Tongliang Liu · Gang Niu · Bo Han · Masashi Sugiyama -
2022 Poster: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning »
Shikun Li · Xiaobo Xia · Hansong Zhang · Yibing Zhan · Shiming Ge · Tongliang Liu -
2022 Poster: Towards Lightweight Black-Box Attack Against Deep Neural Networks »
Chenghao Sun · Yonggang Zhang · Wan Chaoqun · Qizhou Wang · Ya Li · Tongliang Liu · Bo Han · Xinmei Tian -
2022 : Accelerating Perturbed Stochastic Iterates in Asynchronous Lock-Free Optimization »
Kaiwen Zhou · Anthony Man-Cho So · James Cheng -
2022 : Diversity Boosted Learning for Domain Generalization with A Large Number of Domains »
XI LENG · Yatao Bian · Xiaoying Tang -
2022 : Pre-training Robust Feature Extractor Against Clean-label Data Poisoning Attacks »
Ting Zhou · Hanshu Yan · Lei LIU · Jingfeng Zhang · Bo Han -
2023 Poster: SODA: Robust Training of Test-Time Data Adaptors »
Zige Wang · Yonggang Zhang · Zhen Fang · Long Lan · Wenjing Yang · Bo Han -
2023 Poster: Federated Learning with Bilateral Curation for Partially Class-Disjoint Data »
Ziqing Fan · ruipeng zhang · Jiangchao Yao · Bo Han · Ya Zhang · Yanfeng Wang -
2023 Poster: InstanT: Semi-supervised Learning with Instance-dependent Thresholds »
Muyang Li · Runze Wu · Haoyu Liu · Jun Yu · Xun Yang · Bo Han · Tongliang Liu -
2023 Poster: Learning Invariant Molecular Representation in Latent Discrete Space »
Xiang Zhuang · Qiang Zhang · Keyan Ding · Yatao Bian · Xiao Wang · Jingsong Lv · Hongyang Chen · Huajun Chen -
2023 Poster: FedFed: Feature Distillation against Data Heterogeneity in Federated Learning »
Zhiqin Yang · Yonggang Zhang · Yu Zheng · Xinmei Tian · Hao Peng · Tongliang Liu · Bo Han -
2023 Poster: FlatMatch: Bridging Labeled Data and Unlabeled Data with Cross-Sharpness for Semi-Supervised Learning »
Zhuo Huang · Li Shen · Jun Yu · Bo Han · Tongliang Liu -
2023 Poster: Subclass-Dominant Label Noise: A Counterexample for the Success of Early Stopping »
Yingbin Bai · Zhongyi Han · Erkun Yang · Jun Yu · Bo Han · Dadong Wang · Tongliang Liu -
2023 Poster: Combating Representation Learning Disparity with Geometric Harmonization »
Zhihan Zhou · Jiangchao Yao · Feng Hong · Yanfeng Wang · Bo Han · Ya Zhang -
2023 Poster: Understanding and Improving Feature Learning for Out-of-Distribution Generalization »
Yongqiang Chen · Wei Huang · Kaiwen Zhou · Yatao Bian · Bo Han · James Cheng -
2023 Poster: Combating Bilateral Edge Noise for Robust Link Prediction »
Zhanke Zhou · Jiangchao Yao · Jiaxu Liu · Xiawei Guo · Quanming Yao · LI He · Liang Wang · Bo Zheng · Bo Han -
2023 Poster: Diversified Outlier Exposure for Out-of-Distribution Detection via Informative Extrapolation »
Jianing Zhu · Yu Geng · Jiangchao Yao · Tongliang Liu · Gang Niu · Masashi Sugiyama · Bo Han -
2023 Poster: Simplifying and Empowering Transformers for Large-Graph Representations »
Qitian Wu · Wentao Zhao · Chenxiao Yang · Hengrui Zhang · Fan Nie · Haitian Jiang · Yatao Bian · Junchi Yan -
2023 Poster: Learning to Augment Distributions for Out-of-distribution Detection »
Qizhou Wang · Zhen Fang · Yonggang Zhang · Feng Liu · Yixuan Li · Bo Han -
2023 Poster: Eliminating Catastrophic Overfitting Via Abnormal Adversarial Examples Regularization »
Runqi Lin · Chaojian Yu · Tongliang Liu -
2023 Poster: An Efficient Dataset Condensation Plugin and Its Application to Continual Learning »
Enneng Yang · Li Shen · Zhenyi Wang · Tongliang Liu · Guibing Guo -
2023 Poster: CS-Isolate: Extracting Hard Confident Examples by Content and Style Isolation »
Yexiong Lin · Yu Yao · Xiaolong Shi · Mingming Gong · Xu Shen · Dong Xu · Tongliang Liu -
2023 Poster: Invariant Learning via Probability of Sufficient and Necessary Causes »
Mengyue Yang · Yonggang Zhang · Zhen Fang · Yali Du · Furui Liu · Jean-Francois Ton · Jianhong Wang · Jun Wang -
2023 Poster: Does Invariant Graph Learning via Environment Augmentation Learn Invariance? »
Yongqiang Chen · Yatao Bian · Kaiwen Zhou · Binghui Xie · Bo Han · James Cheng -
2023 Poster: Fairness-guided Few-shot Prompting for Large Language Models »
Huan Ma · Changqing Zhang · Yatao Bian · Lemao Liu · Zhirui Zhang · Peilin Zhao · Shu Zhang · Huazhu Fu · Qinghua Hu · Bingzhe Wu -
2023 Poster: Towards Label-free Scene Understanding by Vision Foundation Models »
Runnan Chen · Youquan Liu · Lingdong Kong · Nenglun Chen · Xinge ZHU · Yuexin Ma · Tongliang Liu · Wenping Wang -
2023 Poster: Out-of-distribution Detection Learning with Unreliable Out-of-distribution Sources »
Haotian Zheng · Qizhou Wang · Zhen Fang · Xiaobo Xia · Feng Liu · Tongliang Liu · Bo Han -
2023 Poster: Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training »
Zhenyi Wang · Li Shen · Tongliang Liu · Tiehang Duan · Yanjun Zhu · Donglin Zhan · DAVID DOERMANN · Mingchen Gao -
2022 Spotlight: Lightning Talks 6A-4 »
Xiu-Shen Wei · Konstantina Dritsa · Guillaume Huguet · ABHRA CHAUDHURI · Zhenbin Wang · Kevin Qinghong Lin · Yutong Chen · Jianan Zhou · Yongsen Mao · Junwei Liang · Jinpeng Wang · Mao Ye · Yiming Zhang · Aikaterini Thoma · H.-Y. Xu · Daniel Sumner Magruder · Enwei Zhang · Jianing Zhu · Ronglai Zuo · Massimiliano Mancini · Hanxiao Jiang · Jun Zhang · Fangyun Wei · Faen Zhang · Ioannis Pavlopoulos · Zeynep Akata · Xiatian Zhu · Jingfeng ZHANG · Alexander Tong · Mattia Soldan · Chunhua Shen · Yuxin Peng · Liuhan Peng · Michael Wray · Tongliang Liu · Anjan Dutta · Yu Wu · Oluwadamilola Fasina · Panos Louridas · Angel Chang · Manik Kuchroo · Manolis Savva · Shujie LIU · Wei Zhou · Rui Yan · Gang Niu · Liang Tian · Bo Han · Eric Z. XU · Guy Wolf · Yingying Zhu · Brian Mak · Difei Gao · Masashi Sugiyama · Smita Krishnaswamy · Rong-Cheng Tu · Wenzhe Zhao · Weijie Kong · Chengfei Cai · WANG HongFa · Dima Damen · Bernard Ghanem · Wei Liu · Mike Zheng Shou -
2022 Spotlight: Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks »
Jianan Zhou · Jianing Zhu · Jingfeng ZHANG · Tongliang Liu · Gang Niu · Bo Han · Masashi Sugiyama -
2022 Spotlight: Lightning Talks 5B-3 »
Yanze Wu · Jie Xiao · Nianzu Yang · Jieyi Bi · Jian Yao · Yiting Chen · Qizhou Wang · Yangru Huang · Yongqiang Chen · Peixi Peng · Yuxin Hong · Xintao Wang · Feng Liu · Yining Ma · Qibing Ren · Xueyang Fu · Yonggang Zhang · Kaipeng Zeng · Jiahai Wang · GEN LI · Yonggang Zhang · Qitian Wu · Yifan Zhao · Chiyu Wang · Junchi Yan · Feng Wu · Yatao Bian · Xiaosong Jia · Ying Shan · Zhiguang Cao · Zheng-Jun Zha · Guangyao Chen · Tianjun Xiao · Han Yang · Jing Zhang · Jinbiao Chen · MA Kaili · Yonghong Tian · Junchi Yan · Chen Gong · Tong He · Binghui Xie · Yuan Sun · Francesco Locatello · Tongliang Liu · Yeow Meng Chee · David P Wipf · Tongliang Liu · Bo Han · Bo Han · Yanwei Fu · James Cheng · Zheng Zhang -
2022 Spotlight: Watermarking for Out-of-distribution Detection »
Qizhou Wang · Feng Liu · Yonggang Zhang · Jing Zhang · Chen Gong · Tongliang Liu · Bo Han -
2022 Spotlight: Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs »
Yongqiang Chen · Yonggang Zhang · Yatao Bian · Han Yang · MA Kaili · Binghui Xie · Tongliang Liu · Bo Han · James Cheng -
2022 Spotlight: Lightning Talks 4A-2 »
Barakeel Fanseu Kamhoua · Hualin Zhang · Taiki Miyagawa · Tomoya Murata · Xin Lyu · Yan Dai · Elena Grigorescu · Zhipeng Tu · Lijun Zhang · Taiji Suzuki · Wei Jiang · Haipeng Luo · Lin Zhang · Xi Wang · Young-San Lin · Huan Xiong · Liyu Chen · Bin Gu · Jinfeng Yi · Yongqiang Chen · Sandeep Silwal · Yiguang Hong · Maoyuan Song · Lei Wang · Tianbao Yang · Han Yang · MA Kaili · Samson Zhou · Deming Yuan · Bo Han · Guodong Shi · Bo Li · James Cheng -
2022 Spotlight: Exact Shape Correspondence via 2D graph convolution »
Barakeel Fanseu Kamhoua · Lin Zhang · Yongqiang Chen · Han Yang · MA Kaili · Bo Han · Bo Li · James Cheng -
2022 Spotlight: RSA: Reducing Semantic Shift from Aggressive Augmentations for Self-supervised Learning »
Yingbin Bai · Erkun Yang · Zhaoqing Wang · Yuxuan Du · Bo Han · Cheng Deng · Dadong Wang · Tongliang Liu -
2022 Spotlight: Lightning Talks 2B-4 »
Feiyi Xiao · Amrutha Saseendran · Kwangho Kim · Keyu Yan · Changjian Shui · Guangxi Li · Shikun Li · Edward Kennedy · Man Zhou · Gezheng Xu · Ruilin Ye · Xiaobo Xia · Junjie Tang · Kathrin Skubch · Stefan Falkner · Hansong Zhang · Jose Zubizarreta · Huaying Fang · Xuanqiang Zhao · Jie Huang · Qi CHEN · Yibing Zhan · Jiaqi Li · Xin Wang · Ruibin Xi · Feng Zhao · Margret Keuper · Charles Ling · Shiming Ge · Chengjun Xie · Tongliang Liu · Tal Arbel · Chongyi Li · Danfeng Hong · Boyu Wang · Christian Gagné -
2022 Spotlight: Lightning Talks 2B-3 »
Jie-Jing Shao · Jiangmeng Li · Jiashuo Liu · Zongbo Han · Tianyang Hu · Jiayun Wu · Wenwen Qiang · Jun WANG · Zhipeng Liang · Lan-Zhe Guo · Wenjia Wang · Yanan Zhang · Xiao-wen Yang · Fan Yang · Bo Li · Wenyi Mo · Zhenguo Li · Liu Liu · Peng Cui · Yu-Feng Li · Changwen Zheng · Lanqing Li · Yatao Bian · Bing Su · Hui Xiong · Peilin Zhao · Bingzhe Wu · Changqing Zhang · Jianhua Yao -
2022 Spotlight: UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup »
Zongbo Han · Zhipeng Liang · Fan Yang · Liu Liu · Lanqing Li · Yatao Bian · Peilin Zhao · Bingzhe Wu · Changqing Zhang · Jianhua Yao -
2022 Spotlight: Estimating Noise Transition Matrix with Label Correlations for Noisy Multi-Label Learning »
Shikun Li · Xiaobo Xia · Hansong Zhang · Yibing Zhan · Shiming Ge · Tongliang Liu -
2022 Panel: Panel 1C-1: Learning Neural Set… & Holomorphic Equilibrium Propagation… »
Axel Laborieux · Yatao Bian -
2022 Poster: MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models »
Erdun Gao · Ignavier Ng · Mingming Gong · Li Shen · Wei Huang · Tongliang Liu · Kun Zhang · Howard Bondell -
2022 Poster: Watermarking for Out-of-distribution Detection »
Qizhou Wang · Feng Liu · Yonggang Zhang · Jing Zhang · Chen Gong · Tongliang Liu · Bo Han -
2022 Poster: Exact Shape Correspondence via 2D graph convolution »
Barakeel Fanseu Kamhoua · Lin Zhang · Yongqiang Chen · Han Yang · MA Kaili · Bo Han · Bo Li · James Cheng -
2022 Poster: Counterfactual Fairness with Partially Known Causal Graph »
Aoqi Zuo · Susan Wei · Tongliang Liu · Bo Han · Kun Zhang · Mingming Gong -
2022 Poster: Out-of-Distribution Detection with An Adaptive Likelihood Ratio on Informative Hierarchical VAE »
Yewen Li · Chaojie Wang · Xiaobo Xia · Tongliang Liu · xin miao · Bo An -
2022 Poster: Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization »
De Cheng · Yixiong Ning · Nannan Wang · Xinbo Gao · Heng Yang · Yuxuan Du · Bo Han · Tongliang Liu -
2022 Poster: Synergy-of-Experts: Collaborate to Improve Adversarial Robustness »
Sen Cui · Jingfeng ZHANG · Jian Liang · Bo Han · Masashi Sugiyama · Changshui Zhang -
2022 Poster: Pluralistic Image Completion with Gaussian Mixture Models »
Xiaobo Xia · Wenhao Yang · Jie Ren · Yewen Li · Yibing Zhan · Bo Han · Tongliang Liu -
2022 Poster: Learning Neural Set Functions Under the Optimal Subset Oracle »
Zijing Ou · Tingyang Xu · Qinliang Su · Yingzhen Li · Peilin Zhao · Yatao Bian -
2022 Poster: UMIX: Improving Importance Weighting for Subpopulation Shift via Uncertainty-Aware Mixup »
Zongbo Han · Zhipeng Liang · Fan Yang · Liu Liu · Lanqing Li · Yatao Bian · Peilin Zhao · Bingzhe Wu · Changqing Zhang · Jianhua Yao -
2022 Poster: Is Out-of-Distribution Detection Learnable? »
Zhen Fang · Yixuan Li · Jie Lu · Jiahua Dong · Bo Han · Feng Liu -
2021 Poster: Understanding and Improving Early Stopping for Learning with Noisy Labels »
Yingbin Bai · Erkun Yang · Bo Han · Yanhua Yang · Jiatong Li · Yinian Mao · Gang Niu · Tongliang Liu -
2021 Poster: Not All Low-Pass Filters are Robust in Graph Convolutional Networks »
Heng Chang · Yu Rong · Tingyang Xu · Yatao Bian · Shiji Zhou · Xin Wang · Junzhou Huang · Wenwu Zhu -
2021 Poster: Universal Semi-Supervised Learning »
Zhuo Huang · Chao Xue · Bo Han · Jian Yang · Chen Gong -
2021 Poster: Probabilistic Margins for Instance Reweighting in Adversarial Training »
qizhou wang · Feng Liu · Bo Han · Tongliang Liu · Chen Gong · Gang Niu · Mingyuan Zhou · Masashi Sugiyama -
2021 Poster: Instance-dependent Label-noise Learning under a Structural Causal Model »
Yu Yao · Tongliang Liu · Mingming Gong · Bo Han · Gang Niu · Kun Zhang -
2021 Poster: TOHAN: A One-step Approach towards Few-shot Hypothesis Adaptation »
Haoang Chi · Feng Liu · Wenjing Yang · Long Lan · Tongliang Liu · Bo Han · William Cheung · James Kwok -
2021 Poster: Confident Anchor-Induced Multi-Source Free Domain Adaptation »
Jiahua Dong · Zhen Fang · Anjin Liu · Gan Sun · Tongliang Liu -
2020 Poster: Dual T: Reducing Estimation Error for Transition Matrix in Label-noise Learning »
Yu Yao · Tongliang Liu · Bo Han · Mingming Gong · Jiankang Deng · Gang Niu · Masashi Sugiyama -
2020 Poster: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
Xiaobo Xia · Tongliang Liu · Bo Han · Nannan Wang · Mingming Gong · Haifeng Liu · Gang Niu · Dacheng Tao · Masashi Sugiyama -
2020 Spotlight: Part-dependent Label Noise: Towards Instance-dependent Label Noise »
Xiaobo Xia · Tongliang Liu · Bo Han · Nannan Wang · Mingming Gong · Haifeng Liu · Gang Niu · Dacheng Tao · Masashi Sugiyama -
2020 Poster: Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates »
Kaiwen Zhou · Anthony Man-Cho So · James Cheng -
2020 Poster: Domain Generalization via Entropy Regularization »
Shanshan Zhao · Mingming Gong · Tongliang Liu · Huan Fu · Dacheng Tao -
2019 Poster: Are Anchor Points Really Indispensable in Label-Noise Learning? »
Xiaobo Xia · Tongliang Liu · Nannan Wang · Bo Han · Chen Gong · Gang Niu · Masashi Sugiyama -
2019 Poster: Control Batch Size and Learning Rate to Generalize Well: Theoretical and Empirical Evidence »
Fengxiang He · Tongliang Liu · Dacheng Tao -
2018 Poster: Norm-Ranging LSH for Maximum Inner Product Search »
Xiao Yan · Jinfeng Li · Xinyan Dai · Hongzhi Chen · James Cheng -
2017 Poster: Accelerated First-order Methods for Geodesically Convex Optimization on Riemannian Manifolds »
Yuanyuan Liu · Fanhua Shang · James Cheng · Hong Cheng · Licheng Jiao -
2014 Poster: Generalized Higher-Order Orthogonal Iteration for Tensor Decomposition and Completion »
Yuanyuan Liu · Fanhua Shang · Wei Fan · James Cheng · Hong Cheng