Mind the Label Shift of Augmentation-based Graph OOD Generalization

27 March 2023

Jian Liang

Papers citing "Mind the Label Shift of Augmentation-based Graph OOD Generalization"

40 / 40 papers shown

Title
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning Puning Yang Qizhou Wang Zhuo Huang Tongliang Liu Chengqi Zhang Bo Han MU 107 0 0 17 May 2025
GOLD: Graph Out-of-Distribution Detection via Implicit Adversarial Latent Generation Danny Wang Ruihong Qiu Guangdong Bai Zi Huang 363 3 0 09 Feb 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 240 3 0 07 Jan 2025
Subgraph Aggregation for Out-of-Distribution Generalization on Graphs Bowen Liu Haoyang Li Shuning Wang Shuo Nie Shanghang Zhang OODD CML 153 0 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 131 5 0 25 Oct 2024
A Survey of Trustworthy Graph Learning: Reliability, Explainability, and Privacy Protection Bingzhe Wu Jintang Li Junchi Yu Yatao Bian Hengtong Zhang ... Guangyu Sun Peng Cui Zibin Zheng Zhe Liu P. Zhao OOD 92 28 0 20 May 2022
Out-Of-Distribution Generalization on Graphs: A Survey Haoyang Li Xin Eric Wang Ziwei Zhang Wenwu Zhu OOD CML 110 101 0 16 Feb 2022
Discovering Invariant Rationales for Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xiangnan He Tat-Seng Chua OOD AI4CE 155 231 0 30 Jan 2022
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 149 535 0 31 Aug 2021
Towards Efficient Point Cloud Graph Neural Networks Through Architectural Simplification Shyam A. Tailor R. D. Jong Tiago Azevedo Matthew Mattina Partha P. Maji 3DPC GNN 43 12 0 13 Aug 2021
Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization Kartik Ahuja Ethan Caballero Dinghuai Zhang Jean-Christophe Gagnon-Audet Yoshua Bengio Ioannis Mitliagkas Irina Rish OOD 62 269 0 11 Jun 2021
Recognizing Predictive Substructures with Subgraph Information Bottleneck Junchi Yu Tingyang Xu Yu Rong Yatao Bian Junzhou Huang Ran He 61 45 0 20 Mar 2021
Size-Invariant Graph Representations for Graph Classification Extrapolations Beatrice Bevilacqua Yangze Zhou Bruno Ribeiro OOD 98 110 0 08 Mar 2021
Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization Aseem Baranwal Kimon Fountoulakis Aukosh Jagannath OODD 113 76 0 13 Feb 2021
Graph Neural Networks in Recommender Systems: A Survey Shiwen Wu Fei Sun Wentao Zhang Xu Xie Tengjiao Wang GNN 153 1,230 0 04 Nov 2020
Environment Inference for Invariant Learning Elliot Creager J. Jacobsen R. Zemel OOD 61 383 0 14 Oct 2020
Graph Information Bottleneck for Subgraph Recognition Junchi Yu Tingyang Xu Yu Rong Yatao Bian Junzhou Huang Ran He 47 157 0 12 Oct 2020
Energy-based Out-of-distribution Detection Weitang Liu Xiaoyun Wang John Douglas Owens Yixuan Li OODD 271 1,366 0 08 Oct 2020
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization Qi Zhu Carl Yang Yidan Xu Haonan Wang Chao Zhang Jiawei Han 100 120 0 11 Sep 2020
Simple and Deep Graph Convolutional Networks Ming Chen Zhewei Wei Zengfeng Huang Bolin Ding Yaliang Li GNN 121 1,486 0 04 Jul 2020
Graph Structure Learning for Robust Graph Neural Networks Wei Jin Yao Ma Xiaorui Liu Xianfeng Tang Suhang Wang Jiliang Tang OOD AAML 84 706 0 20 May 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 306 2,732 0 02 May 2020
Rumor Detection on Social Media with Bi-Directional Graph Convolutional Networks Tian Bian Xi Xiao Tingyang Xu P. Zhao Wenbing Huang Yu Rong Junzhou Huang GNN 64 599 0 17 Jan 2020
Your Classifier is Secretly an Energy Based Model and You Should Treat it Like One Will Grathwohl Kuan-Chieh Wang J. Jacobsen David Duvenaud Mohammad Norouzi Kevin Swersky VLM 85 546 0 06 Dec 2019
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization Shiori Sagawa Pang Wei Koh Tatsunori B. Hashimoto Percy Liang OOD 108 1,243 0 20 Nov 2019
Multi-scale Attributed Node Embedding Benedek Rozemberczki Carl Allen Rik Sarkar GNN 266 863 0 28 Sep 2019
A Restricted Black-box Adversarial Framework Towards Attacking Graph Embedding Models Heng Chang Yu Rong Tingyang Xu Wenbing Huang Honglei Zhang Peng Cui Wenwu Zhu Junzhou Huang AAML 70 153 0 04 Aug 2019
Graph U-Nets Hongyang Gao Shuiwang Ji AI4CE SSL SSeg GNN 132 1,092 0 11 May 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 150 1,328 0 10 Mar 2019
Simplifying Graph Convolutional Networks Felix Wu Tianyi Zhang Amauri Souza Christopher Fifty Tao Yu Kilian Q. Weinberger GNN 244 3,179 0 19 Feb 2019
Predict then Propagate: Graph Neural Networks meet Personalized PageRank Johannes Klicpera Aleksandar Bojchevski Stephan Günnemann GNN 222 1,691 0 14 Oct 2018
How Powerful are Graph Neural Networks? Keyulu Xu Weihua Hu J. Leskovec Stefanie Jegelka GNN 243 7,681 0 01 Oct 2018
Generalizing to Unseen Domains via Adversarial Data Augmentation Riccardo Volpi Hongseok Namkoong Ozan Sener John C. Duchi Vittorio Murino Silvio Savarese OOD 119 784 0 30 May 2018
AutoAugment: Learning Augmentation Policies from Data E. D. Cubuk Barret Zoph Dandelion Mané Vijay Vasudevan Quoc V. Le 133 1,774 0 24 May 2018
Robust Optimization over Multiple Domains Qi Qian Shenghuo Zhu Jiasheng Tang Rong Jin Baigui Sun Hao Li OOD 74 71 0 19 May 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 352 1,369 0 12 Feb 2018
Inductive Representation Learning on Large Graphs William L. Hamilton Z. Ying J. Leskovec 509 15,300 0 07 Jun 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 179 593 0 22 May 2017
Categorical Reparameterization with Gumbel-Softmax Eric Jang S. Gu Ben Poole BDL 344 5,372 0 03 Nov 2016
Causal inference using invariant prediction: identification and confidence intervals J. Peters Peter Buhlmann N. Meinshausen OOD 122 973 0 06 Jan 2015