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NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs


Aug 22, 2022
Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh V. Chawla


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Heterogeneous Graph Masked Autoencoders


Aug 21, 2022
Yijun Tian, Kaiwen Dong, Chunhui Zhang, Chuxu Zhang, Nitesh V. Chawla


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Graph-based Molecular Representation Learning


Jul 08, 2022
Zhichun Guo, Bozhao Nan, Yijun Tian, Olaf Wiest, Chuxu Zhang, Nitesh V. Chawla


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Deep Ensembles for Graphs with Higher-order Dependencies


May 27, 2022
Steven J. Krieg, William C. Burgis, Patrick M. Soga, Nitesh V. Chawla

* 24 pages 

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Recipe2Vec: Multi-modal Recipe Representation Learning with Graph Neural Networks


May 24, 2022
Yijun Tian, Chuxu Zhang, Zhichun Guo, Yihong Ma, Ronald Metoyer, Nitesh V. Chawla

* Accepted by IJCAI 2022 

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RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation


May 24, 2022
Yijun Tian, Chuxu Zhang, Zhichun Guo, Chao Huang, Ronald Metoyer, Nitesh V. Chawla

* Accepted by IJCAI 2022 

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Few-Shot Learning on Graphs: A Survey


Mar 17, 2022
Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu


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Predicting Terrorist Attacks in the United States using Localized News Data


Jan 14, 2022
Steven J. Krieg, Christian W. Smith, Rusha Chatterjee, Nitesh V. Chawla


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Graph Barlow Twins: A self-supervised representation learning framework for graphs


Jun 04, 2021
Piotr Bielak, Tomasz Kajdanowicz, Nitesh V. Chawla


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DeepSMOTE: Fusing Deep Learning and SMOTE for Imbalanced Data


May 05, 2021
Damien Dablain, Bartosz Krawczyk, Nitesh V. Chawla

* 14 pages, 9 figures 

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