| Inductive representation learning on large graphs W Hamilton, Z Ying, J Leskovec Advances in neural information processing systems 30, 2017 | 15316 | 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 | 3628 | 2018 |
| Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584, 2017 | 2381 | 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 | 1691 | 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 | 1298 | 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 | 1025 | 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 | 1021 | 2020 |
| 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 | 987 | 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, 2018 | 811 | 2018 |
| Hyperbolic graph convolutional neural networks I Chami, Z Ying, C Ré, J Leskovec Advances in neural information processing systems 32, 2019 | 642 | 2019 |
| Position-aware graph neural networks J You, R Ying, J Leskovec International conference on machine learning, 7134-7143, 2019 | 527 | 2019 |
| Design space for graph neural networks J You, Z Ying, J Leskovec Advances in Neural Information Processing Systems 33, 17009-17021, 2020 | 319 | 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 | 221 | 2021 |
| Neural execution of graph algorithms P Veličković, R Ying, M Padovano, R Hadsell, C Blundell arXiv preprint arXiv:1910.10593, 2019 | 169 | 2019 |
| Multi-hop attention graph neural network G Wang, R Ying, J Huang, J Leskovec International Joint Conferences on Artificial Intelligence 2020, 2020 | 103 | 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 | 97 | 2022 |
| Improving graph attention networks with large margin-based constraints G Wang, R Ying, J Huang, J Leskovec arXiv preprint arXiv:1910.11945, 2019 | 83 | 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 | 82 | 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 | 77 | 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 | 76 | 2024 |
Jure LeskovecProfessor of Computer Science, Stanford University在 cs.stanford.edu 的电子邮件经过验证
