| Deep graph library: A graph-centric, highly-performant package for graph neural networks M Wang, D Zheng, Z Ye, Q Gan, M Li, X Song, J Zhou, C Ma, L Yu, Y Gai, ... arXiv preprint arXiv:1909.01315, 2019 | 1211 | 2019 |
| Deep graph library: Towards efficient and scalable deep learning on graphs M Wang, L Yu, D Zheng, Q Gan, Y Gai, Z Ye, M Li, J Zhou, Q Huang, C Ma, ... ICLR workshop on representation learning on graphs and manifolds, 2019 | 759 | 2019 |
| Dgl-lifesci: An open-source toolkit for deep learning on graphs in life science M Li, J Zhou, J Hu, W Fan, Y Zhang, Y Gu, G Karypis ACS Omega, 2021 | 142 | 2021 |
| Drkg-drug repurposing knowledge graph for covid-19 VN Ioannidis, X Song, S Manchanda, M Li, X Pan, D Zheng, X Ning, ... https://github.com/gnn4dr/DRKG, 2020 | 113* | 2020 |
| A knowledge graph of clinical trials (CTKG) Z Chen, B Peng, VN Ioannidis, M Li, G Karypis, X Ning Scientific reports 12 (1), 4724, 2022 | 16* | 2022 |
| Benchmarking Accuracy and Generalizability of Four Graph Neural Networks Using Large In Vitro ADME Datasets from Different Chemical Spaces F Broccatelli, R Trager, M Reutlinger, G Karypis, M Li Molecular Informatics (top 10 most-cited papers, 2022 - 2023), 2022 | 14 | 2022 |
| De novo generation of dual-target ligands using adversarial training and reinforcement learning F Lu, M Li, X Min, C Li, X Zeng Briefings in Bioinformatics 22 (6), bbab333, 2021 | 13 | 2021 |
| A statistical characterization of attentions in graph neural networks M Li, H Zhang, X Shi, M Wang, Z Zhang International Conference on Learning Representations (ICLR) 2019 Workshop on …, 2019 | 7 | 2019 |
| GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? M Li, E Kreačić, VK Potluru, P Li arXiv preprint arXiv:2310.13833, 2023 | 4 | 2023 |
| Graph Neural Networks in Life Sciences: Opportunities and Solutions Z Wang, VN Ioannidis, H Rangwala, T Arai, R Brand, M Li, Y Nakayama Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 3 | 2022 |
| Opportunities and challenges of graph neural networks in electrical engineering E Chien, M Li, A Aportela, K Ding, S Jia, S Maji, Z Zhao, J Duarte, V Fung, ... Nature Reviews Electrical Engineering, 1-18, 2024 | | 2024 |
| KGExplainer: Towards Exploring Connected Subgraph Explanations for Knowledge Graph Completion T Ma, W Tao, M Li, J Zhang, X Pan, J Lin, B Song, X Zeng arXiv preprint arXiv:2404.03893, 2024 | | 2024 |
| LayerDAG: A Layerwise Autoregressive Diffusion Model of Directed Acyclic Graphs for System M Li, V Shitole, E Chien, C Man, Z Wang, Y Zhang, T Krishna, P Li ISCA Workshop on Machine Learning for Computer Architecture and Systems 2024, 2024 | | 2024 |
George KarypisDistinguished McKnight University Professor, University of Minnesota; SPS, AWS在 umn.edu 的电子邮件经过验证
