| On the opportunities and risks of foundation models R Bommasani, DA Hudson, E Adeli, R Altman, S Arora, S von Arx, ... arXiv preprint arXiv:2108.07258, 2021 | 4759 | 2021 |
| 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 (NeurIPS 2018), 2018 | 2687* | 2018 |
| GNNExplainer: Generating explanations for graph neural networks Z Ying, D Bourgeois, J You, M Zitnik, J Leskovec Advances in Neural Information Processing Systems (NeurIPS 2019), 2019 | 1868 | 2019 |
| GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models J You, R Ying, X Ren, WL Hamilton, J Leskovec International Conference on Machine Learning (ICML 2018), 2018 | 1148 | 2018 |
| Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation J You, B Liu, R Ying, V Pande, J Leskovec Advances in Neural Information Processing Systems (NeurIPS 2018), 2018 | 1137 | 2018 |
| Deep Gaussian Process for Crop Yield Prediction Based on Remote Sensing Data. J You, X Li, M Low, D Lobell, S Ermon AAAI Conference on Artificial Intelligence (AAAI 2017), 2017 | 650 | 2017 |
| Position-aware Graph Neural Networks J You, R Ying, J Leskovec International Conference on Machine Learning (ICML 2019), 2019 | 598 | 2019 |
| Design space for graph neural networks J You, Z Ying, J Leskovec Advances in Neural Information Processing Systems (NeurIPS 2020), 2020 | 411 | 2020 |
| Identity-aware Graph Neural Networks J You, J Gomes-Selman, R Ying, J Leskovec AAAI Conference on Artificial Intelligence (AAAI 2021), 2021 | 281 | 2021 |
| Handling Missing Data with Graph Representation Learning J You, X Ma, DY Ding, M Kochenderfer, J Leskovec Advances in Neural Information Processing Systems (NeurIPS 2020), 2020 | 219 | 2020 |
| Graph Structure of Neural Networks J You, J Leskovec, K He, S Xie International Conference on Machine Learning (ICML 2020), 2020 | 179 | 2020 |
| ROLAND: graph learning framework for dynamic graphs J You, T Du, J Leskovec Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 175 | 2022 |
| Hierarchical Temporal Convolutional Networks for Dynamic Recommender Systems J You, Y Wang, A Pal, P Eksombatchai, C Rosenburg, J Leskovec The Web Conference 2019 (WWW 2019), 2019 | 157 | 2019 |
| Neural subgraph matching Z Ying, A Wang, J You, C Wen, A Canedo, J Leskovec | 105* | 2020 |
| Redundancy-Free Computation for Graph Neural Networks Z Jia, S Lin, R Ying, J You, A Porter, J Leskovec, A Aiken ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2020), 0 | 101* | |
| Nemotron-4 340b technical report B Adler, N Agarwal, A Aithal, DH Anh, P Bhattacharya, A Brundyn, ... arXiv preprint arXiv:2406.11704, 2024 | 65 | 2024 |
| G2SAT: Learning to Generate SAT Formulas J You, H Wu, C Barrett, R Ramanujan, J Leskovec Advances in Neural Information Processing Systems (NeurIPS 2019), 2019 | 51 | 2019 |
| Inductive learning on commonsense knowledge graph completion B Wang, G Wang, J Huang, J You, J Leskovec, CCJ Kuo 2021 international joint conference on neural networks (IJCNN), 1-8, 2021 | 42 | 2021 |
| Relational deep learning: Graph representation learning on relational databases M Fey, W Hu, K Huang, JE Lenssen, R Ranjan, J Robinson, R Ying, J You, ... arXiv preprint arXiv:2312.04615, 2023 | 20* | 2023 |
| Nemotron-4 15b technical report J Parmar, S Prabhumoye, J Jennings, M Patwary, S Subramanian, D Su, ... arXiv preprint arXiv:2402.16819, 2024 | 19 | 2024 |
Jure LeskovecProfessor of Computer Science, Stanford Universityبريد إلكتروني تم التحقق منه على cs.stanford.edu