Wei Jin

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Citations	2233	2231
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Jiliang TangUniversity Foundation Professor of Computer Science and Engineering, Michigan State UniversityVerified email at msu.edu
Yao MaAssistant Professor of Computer Science, Rensselaer Polytechnic InstituteVerified email at rpi.edu
Xiaorui LiuAssistant Professor of Computer Science, North Carolina State UniversityVerified email at ncsu.edu
Han XuPhD Student, Michigan State UniversityVerified email at msu.edu
Suhang WangPennsylvania State UniversityVerified email at psu.edu
Yaxin LiMichigan State UniversityVerified email at msu.edu
Neil ShahResearch Scientist at SnapVerified email at snap.com
Xianfeng TangAmazonVerified email at amazon.com
Hongzhi WenMichigan State UniversityVerified email at msu.edu
Jiayuan DingVMwareVerified email at vmware.com
Zitao LiuJinan University, Guangzhou, ChinaVerified email at jnu.edu.cn
Tyler DerrVanderbilt UniversityVerified email at vanderbilt.edu
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
Yozen LiuSnap Inc.Verified email at snapchat.com
Yuying Xie (谢於颖)Associate Professor at Michigan State UniversityVerified email at msu.edu
Haochen LiuFidelity Investments, AI Center of ExcellenceVerified email at msu.edu
Wenqi FANAssistant Professor, The Hong Kong Polytechnic UniversityVerified email at my.cityu.edu.hk
Tong ZhaoResearch Scientist at SnapVerified email at snap.com
Lingxiao ZhaoCarnegie Mellon UniversityVerified email at andrew.cmu.edu
Haitao MaoMichigan State UniversityVerified email at msu.edu

Wei Jin

Assistant Professor, Emory University

Verified email at emory.edu - Homepage

Data Mining Graph Neural Networks Machine Learning Data-Centric AI


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Graph Structure Learning for Robust Graph Neural Networks W Jin, Y Ma, X Liu, X Tang, S Wang, J Tang KDD 2020, 2020	436	2020
Traffic flow prediction via spatial temporal graph neural network X Wang, Y Ma, Y Wang, W Jin, X Wang, J Tang, C Jia, J Yu Proceedings of the web conference 2020, 1082-1092, 2020	370	2020
Adversarial attacks and defenses on graphs W Jin, Y Li, H Xu, Y Wang, S Ji, C Aggarwal, J Tang ACM SIGKDD Explorations Newsletter 22 (2), 19-34, 2021	222*	2021
Node Similarity Preserving Graph Convolutional Networks W Jin, T Derr, Y Wang, Y Ma, Z Liu, J Tang International Conference on Web Search and Data Mining (WSDM), 2021	170	2021
Self-supervised learning on graphs: Deep insights and new direction W Jin, T Derr, H Liu, Y Wang, S Wang, Z Liu, J Tang arXiv preprint, 2020	167	2020
Deeprobust: a platform for adversarial attacks and defenses Y Li, W Jin, H Xu, J Tang Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 16078 …, 2021	123*	2021
Elastic graph neural networks X Liu, W Jin, Y Ma, Y Li, H Liu, Y Wang, M Yan, J Tang International Conference on Machine Learning (ICML), 6837-6849, 2021	89	2021
From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness L Zhao, W Jin, L Akoglu, N Shah International Conference on Learning Representations (ICLR), 2022	81	2022
Graph Condensation for Graph Neural Networks W Jin, L Zhao, S Zhang, Y Liu, J Tang, N Shah International Conference on Learning Representations (ICLR), 2022	65	2022
Graph Data Augmentation for Graph Machine Learning: A Survey T Zhao, W Jin, Y Wang, G Liu, Y Liu, S Gunnemann, N Shah, M Jiang https://arxiv.org/abs/2202.08871, 2022	62	2022
Graph trend filtering networks for recommendation W Fan, X Liu, W Jin, X Zhao, J Tang, Q Li Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022	53	2022
Automated self-supervised learning for graphs W Jin, X Liu, X Zhao, Y Ma, N Shah, J Tang International Conference on Learning Representations (ICLR), 2022	48	2022
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels E Dai, W Jin, H Liu, S Wang WSDM 2022, 2022	44	2022
Condensing Graphs via One-Step Gradient Matching W Jin, X Tang, H Jiang, Z Li, D Zhang, J Tang, B Yin KDD 2022, 2022	35	2022
Exploring the potential of large language models (llms) in learning on graphs Z Chen, H Mao, H Li, W Jin, H Wen, X Wei, S Wang, D Yin, W Fan, H Liu, ... arXiv preprint arXiv:2307.03393, 2023	30	2023
Graph neural networks with adaptive residual X Liu, J Ding, W Jin, H Xu, Y Ma, Z Liu, J Tang NeurIPS 2021, 2021	30	2021
Graph Neural Networks for Multimodal Single-Cell Data Integration H Wen, J Ding, W Jin, Y Wang, Y Xie, J Tang KDD 2022, 2022	27	2022
Graph neural networks: Self-supervised learning Y Wang, W Jin, T Derr Graph Neural Networks: Foundations, Frontiers, and Applications, 391-420, 2022	23	2022
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective W Jin, X Liu, Y Ma, C Aggarwal, J Tang KDD 2022, 2022	22*	2022
Jointly attacking graph neural network and its explanations W Fan, W Jin, X Liu, H Xu, X Tang, S Wang, Q Li, J Tang, J Wang, ... ICDE 2023, 2021	20	2021

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