| Scientific discovery in the age of artificial intelligence H Wang*, T Fu*, Y Du*, W Gao, K Huang, Z Liu, P Chandak, S Liu, ... Nature 620 (7972), 47-60, 2023 | 1008* | 2023 |
| A Survey on Graph Structure Learning: Progress and Opportunities Y Zhu, W Xu, J Zhang, Y Du, J Zhang, Q Liu, C Yang, S Wu arXiv preprint arXiv:2103.03036, 2021 | 306* | 2021 |
| Structure-based Drug Design with Equivariant Diffusion Models A Schneuing*, Y Du*, C Harris*, A Jamasb, I Igashov, W Du, T Blundell, ... Nature Computational Science, 2022 | 229* | 2022 |
| A Systematic Survey of Chemical Pre-trained Models J Xia, Y Zhu, Y Du, SZ Li Proceedings of the Thirty-Second International Joint Conference on …, 2023 | 143* | 2023 |
| Machine learning-aided generative molecular design Y Du, AR Jamasb, J Guo, T Fu, C Harris, Y Wang, C Duan, P Liò, ... Nature Machine Intelligence, 1-16, 2024 | 128* | 2024 |
| Artificial intelligence for science in quantum, atomistic, and continuum systems X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y Xie, M Liu, Y Lin, Z Xu, K Yan, ... arXiv preprint arXiv:2307.08423, 2023 | 117 | 2023 |
| Deep learning to segment pelvic bones: large-scale CT datasets and baseline models P Liu, H Han, Y Du, H Zhu, Y Li, F Gu, H Xiao, J Li, C Zhao, L Xiao, X Wu, ... International Journal of Computer Assisted Radiology and Surgery 16, 749-756, 2021 | 110* | 2021 |
| A Survey on Deep Graph Generation: Methods and Applications Y Du*, Y Zhu*, Y Wang*, J Zhang, Q Liu, S Wu Proceedings of the First Learning on Graphs Conference 198, 47:1-47:21, 2022 | 95 | 2022 |
| GAUCHE: A Library for Gaussian Processes in Chemistry RR Griffiths, L Klarner, H Moss, A Ravuri, ST Truong, Y Du, AR Jamasb, ... Advances in Neural Information Processing Systems, 2023 | 76* | 2023 |
| SE(3) Equivariant Graph Neural Networks with Complete Local Frames W Du, H Zhang, Y Du, Q Meng, W Chen, B Shao, TY Liu International Conference on Machine Learning, 2022, 2021 | 72* | 2021 |
| Graphein-a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks AR Jamasb, RV Torné, EJ Ma, Y Du, C Harris, K Huang, D Hall, P Lio, ... Advances in Neural Information Processing Systems, 2022 | 66* | 2022 |
| Generating Tertiary Protein Structures via Interpretable Graph Variational Autoencoders X Guo*, Y Du*, S Tadepalli, L Zhao, A Shehu Bioinformatics Advances, 2021 | 53* | 2021 |
| GraphGT: Machine Learning Datasets for Graph Generation and Transformation Y Du, S Wang, X Guo, H Cao, S Hu, J Jiang, A Varala, A Angirekula, ... The 35th Conference on Neural Information Processing Systems (NeurIPS 2021), 2021 | 52 | 2021 |
| Audio-Driven Co-Speech Gesture Video Generation X Liu, Q Wu, H Zhou, Y Du, W Wu, D Lin, Z Liu Advances in Neural Information Processing Systems, 2022 | 43 | 2022 |
| Interpretable Molecular Graph Generation via Monotonic Constraints Y Du, X Guo, A Shehu, L Zhao SIAM International Conference on Data Mining (SDM 2022), 2022 | 41* | 2022 |
| PIPS: Path Integral Stochastic Optimal Control for Path Sampling in Molecular Dynamics L Holdijk*, Y Du*, P Jaini, F Hooft, B Ensing, M Welling Advances in Neural Information Processing Systems, 2022 | 40* | 2022 |
| Accurate transition state generation with an object-aware equivariant elementary reaction diffusion model C Duan, Y Du, H Jia, HJ Kulik Nature Computational Science 3 (12), 1045-1055, 2023 | 38 | 2023 |
| Controllable data generation by deep learning: A review S Wang, Y Du, X Guo, B Pan, Z Qin, L Zhao ACM Computing Surveys, 2024 | 34 | 2024 |
| Property Controllable Variational Autoencoder via Invertible Mutual Dependence X Guo, Y Du, L Zhao The 9th International Conference on Learning Representations (ICLR 2021), 2021 | 34 | 2021 |
| A new perspective on building efficient and expressive 3D equivariant graph neural networks W Du*, Y Du*, L Wang*, D Feng, G Wang, S Ji, CP Gomes, ZM Ma Advances in Neural Information Processing Systems, 2023 | 31* | 2023 |