Zhitao (Rex) Ying

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Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
Jiaxuan YouCS PhD, Stanford UniversityVerified 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
Marinka ZitnikAssistant Professor, Harvard UniversityVerified email at hms.harvard.edu
Dylan BourgeoisVerified email at cs.stanford.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
Bowen Liuinsitro, previously StanfordVerified email at cs.stanford.edu
Vijay PandeAndreessen Horowitz, Stanford UniversityVerified email at stanford.edu
Peter BattagliaResearch Scientist, DeepMindVerified email at google.com
Alvaro Sanchez GonzalezGoogle DeepMindVerified email at google.com
Tobias PfaffDeepMindVerified email at google.com
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
Pankaj K. AgarwalDuke UniversityVerified email at cs.duke.edu
Raia HadsellGoogle DeepMindVerified email at google.com
Charles BlundellResearch Scientist at DeepMindVerified email at google.com

Zhitao (Rex) Ying

Yale University

Verified email at yale.edu - Homepage

Machine learning Graph neural networks Representation Learning Knowledge graph Recommender system


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	10258	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	2633	2018
Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584, 2017	1974	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	1220	2018
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	781	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	737	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	661	2019
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	643	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	619	2018
Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019	441	2019
Position-aware graph neural networks J You, R Ying, J Leskovec International conference on machine learning, 7134-7143, 2019	375	2019
Design space for graph neural networks J You, Z Ying, J Leskovec Advances in Neural Information Processing Systems 33, 17009-17021, 2020	194	2020
Gnn explainer: A tool for post-hoc explanation of graph neural networks R Ying, D Bourgeois, J You, M Zitnik, J Leskovec arXiv preprint arXiv:1903.03894 8, 2019	161	2019
Neural execution of graph algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell arXiv preprint arXiv:1910.10593, 2019	126	2019
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	113	2021
Improving graph attention networks with large margin-based constraints G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:1910.11945, 2019	58	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	51	2020
Multi-hop attention graph neural network G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:2009.14332, 2020	45	2020
Approximating dynamic time warping and edit distance for a pair of point sequences PK Agarwal, K Fox, J Pan, R Ying arXiv preprint arXiv:1512.01876, 2015	35	2015
Direct multi-hop attention based graph neural network G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:2009.14332, 2020	30	2020

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