Rex (Zhitao) Ying

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Jure LeskovecProfessor of Computer Science, Stanford UniversityVerified email at cs.stanford.edu
William L HamiltonAssistant Professor of Computer Science, McGill University and MilaVerified email at cs.mcgill.ca
Jiaxuan YouAssistant Professor, UIUC CSVerified email at cs.stanford.edu
Kaifeng ChenGoogle DeepMind; StanfordVerified email at google.com
Sean (Xiang) RenViterbi Early Career Chair & Associate Professor, University of Southern CaliforniaVerified email at usc.edu
Jing HuangAmazon/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 PfaffGoogle DeepMindVerified email at google.com
Marinka ZitnikAssistant Professor, Harvard UniversityVerified email at hms.harvard.edu
Dylan BourgeoisVerified email at cs.stanford.edu
Bowen LiuAndreessen Horowitz, insitro, 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 google.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	16857	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	3938	2018
Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584, 2017	2498	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	1811	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	1577	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	1162	2020
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	1086	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	1053	2018
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), 2, 2018	843	2018
Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019	710	2019
Position-aware graph neural networks J You, R Ying, J Leskovec International conference on machine learning, 7134-7143, 2019	556	2019
Design space for graph neural networks J You, Z Ying, J Leskovec Advances in Neural Information Processing Systems 33, 17009-17021, 2020	367	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	243	2021
Neural execution of graph algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell arXiv preprint arXiv:1910.10593, 2019	181	2019
Trustllm: Trustworthiness in large language models L Sun, Y Huang, H Wang, S Wu, Q Zhang, C Gao, Y Huang, W Lyu, ... arXiv preprint arXiv:2401.05561, 2024	141	2024
Multi-hop attention graph neural network G Wang, R Ying, J Huang, J Leskovec International Joint Conferences on Artificial Intelligence 2020, 2020	122	2020
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	112	2022
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	94	2020
Improving graph attention networks with large margin-based constraints G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:1910.11945, 2019	91	2019
Folio: Natural language reasoning with first-order logic S Han, H Schoelkopf, Y Zhao, Z Qi, M Riddell, W Zhou, J Coady, D Peng, ... arXiv preprint arXiv:2209.00840, 2022	76	2022

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