Rex (Zhitao) Ying

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Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Jiaxuan YouIncoming Assistant Professor, UIUC CSVerified email at cs.stanford.edu
William L HamiltonAssistant Professor of Computer Science, McGill University and MilaVerified email at cs.mcgill.ca
Kaifeng ChenStanford University; Google ResearchVerified email at google.com
Xiang RenViterbi Early Career Chair & Associate Professor, University of Southern CaliforniaVerified email at usc.edu
Jing HuangAlexa AI/Stanford SAIL/JD AI Research/Apple Siri/IBM ResearchVerified email at amazon.com
Wang GuangtaoUniversity of Michigan, Ann Arbor.Verified email at umich.edu
Peter BattagliaResearch Scientist, DeepMindVerified email at google.com
Alvaro Sanchez GonzalezGoogle DeepMindVerified email at google.com
Tobias PfaffDeepMindVerified email at google.com
Marinka ZitnikAssistant Professor, Harvard UniversityVerified email at hms.harvard.edu
Dylan BourgeoisVerified email at cs.stanford.edu
Bowen Liuinsitro, previously StanfordVerified email at cs.stanford.edu
Vijay PandeAndreessen Horowitz, Stanford UniversityVerified email at stanford.edu
Petar VeličkovićStaff Research Scientist, Google DeepMind | Affiliated Lecturer, University of CambridgeVerified email at deepmind.com
Ines ChamiStanford UniversityVerified email at stanford.edu
Christopher RéComputer Science, Stanford UniversityVerified email at cs.stanford.edu
Raia HadsellGoogle DeepMindVerified email at google.com
Charles BlundellResearch Scientist at DeepMindVerified email at google.com
Pankaj K. AgarwalDuke UniversityVerified email at cs.duke.edu

Rex (Zhitao) Ying

Yale University

Verified email at yale.edu - Homepage

Machine learning Graph learning Hyperbolic representation Foundation models Multimodal models


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Inductive representation learning on large graphs W Hamilton, Z Ying, J Leskovec Advances in neural information processing systems 30, 2017	12665	2017
Graph convolutional neural networks for web-scale recommender systems R Ying, R He, K Chen, P Eksombatchai, WL Hamilton, J Leskovec Proceedings of the 24th ACM SIGKDD international conference on knowledge …, 2018	3122	2018
Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584, 2017	2185	2017
Hierarchical graph representation learning with differentiable pooling Z Ying, J You, C Morris, X Ren, W Hamilton, J Leskovec Advances in neural information processing systems 31, 2018	1445	2018
Gnnexplainer: Generating explanations for graph neural networks Z Ying, D Bourgeois, J You, M Zitnik, J Leskovec Advances in neural information processing systems 32, 2019	1068	2019
Graph convolutional policy network for goal-directed molecular graph generation J You, B Liu, Z Ying, V Pande, J Leskovec Advances in neural information processing systems 31, 2018	902	2018
Graphrnn: Generating realistic graphs with deep auto-regressive models J You, R Ying, X Ren, W Hamilton, J Leskovec International conference on machine learning, 5708-5717, 2018	863	2018
Learning to simulate complex physics with graph networks A Sanchez-Gonzalez, J Godwin, T Pfaff, R Ying, J Leskovec, P Battaglia International conference on machine learning, 8459-8468, 2020	805	2020
Jiaxuan You, Christopher Morris, Xiang Ren, Will Hamilton, and Jure Leskovec. Hierarchical graph representation learning with differentiable pooling Z Ying Advances in neural information processing systems 31, 4800-4810, 2018	707	2018
Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019	544	2019
Position-aware graph neural networks J You, R Ying, J Leskovec International conference on machine learning, 7134-7143, 2019	438	2019
Design space for graph neural networks J You, Z Ying, J Leskovec Advances in Neural Information Processing Systems 33, 17009-17021, 2020	262	2020
Identity-aware graph neural networks J You, JM Gomes-Selman, R Ying, J Leskovec Proceedings of the AAAI conference on artificial intelligence 35 (12), 10737 …, 2021	162	2021
Neural execution of graph algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell arXiv preprint arXiv:1910.10593, 2019	145	2019
Multi-hop attention graph neural network G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:2009.14332, 2020	70	2020
Improving graph attention networks with large margin-based constraints G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:1910.11945, 2019	70	2019
Redundancy-free computation for graph neural networks Z Jia, S Lin, R Ying, J You, J Leskovec, A Aiken Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020	66	2020
Jiaxuan You, Marinka Zitnik, and Jure Leskovec. Gnn explainer: A tool for post-hoc explanation of graph neural networks R Ying, D Bourgeois arXiv preprint arXiv:1903.03894 1, 2019	56	2019
Local augmentation for graph neural networks S Liu, R Ying, H Dong, L Li, T Xu, Y Rong, P Zhao, J Huang, D Wu International Conference on Machine Learning, 14054-14072, 2022	49	2022
Inductive representation learning on large graphs. arXiv 2017 WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1706.02216, 0	39

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