| A 3D generative model for structure-based drug design S Luo, J Guan, J Ma, J Peng Advances in Neural Information Processing Systems 34, 6229-6239, 2021 | 150 | 2021 |
| Pocket2mol: Efficient molecular sampling based on 3d protein pockets X Peng, S Luo, J Guan, Q Xie, J Peng, J Ma International Conference on Machine Learning, 17644-17655, 2022 | 115 | 2022 |
| 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction J Guan, WW Qian, X Peng, Y Su, J Peng, J Ma The Eleventh International Conference on Learning Representations, 2023 | 69 | 2023 |
| Generation of synthetic electronic medical record text J Guan, R Li, S Yu, X Zhang 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 56 | 2018 |
| A method for generating synthetic electronic medical record text J Guan, R Li, S Yu, X Zhang IEEE/ACM transactions on computational biology and bioinformatics 18 (1 …, 2019 | 34 | 2019 |
| Energy-efficient amortized inference with cascaded deep classifiers J Guan, Y Liu, Q Liu, J Peng arXiv preprint arXiv:1710.03368, 2017 | 32 | 2017 |
| Generative hybrid representations for activity forecasting with no-regret learning J Guan, Y Yuan, KM Kitani, N Rhinehart Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 28 | 2020 |
| MolDiff: addressing the atom-bond inconsistency problem in 3D molecule diffusion generation X Peng, J Guan, Q Liu, J Ma arXiv preprint arXiv:2305.07508, 2023 | 21 | 2023 |
| Equivariant point cloud analysis via learning orientations for message passing S Luo, J Li, J Guan, Y Su, C Cheng, J Peng, J Ma Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 21 | 2022 |
| Energy-Inspired Molecular Conformation Optimization J Guan, WW Qian, WY Ma, J Ma, J Peng International Conference on Learning Representations, 2021 | 16 | 2021 |
| DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design J Guan, X Zhou, Y Yang, Y Bao, J Peng, J Ma, Q Liu, L Wang, Q Gu International Conference on Machine Learning, 11827-11846, 2023 | 11 | 2023 |
| Directed weight neural networks for protein structure representation learning J Li arXiv preprint arXiv:2201.13299, 2022 | 7 | 2022 |
| Pocket-specific 3d molecule generation by fragment-based autoregressive diffusion models X Peng, J Guan, J Peng, J Ma | 3 | 2022 |
| Orientation-aware graph neural networks for protein structure representation learning J Li, S Luo, C Deng, C Cheng, J Guan, L Guibas, J Ma, J Peng | 2 | 2022 |
| LinkerNet: Fragment Poses and Linker Co-Design with 3D Equivariant Diffusion J Guan, X Peng, PQ Jiang, Y Luo, J Peng, J Ma Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| Generative Hybrid Representations for Activity Forecasting with No-Regret Learning Supplementary Materials J Guan, Y Yuan, KM Kitani, N Rhinehart | | |
Jian PengHelixon; Previously at UIUC & MITVerified email at helixon.com
