Diffusion Probabilistic Models for 3D Point Cloud Generation S Luo, W Hu IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 703 | 2021 |
High-resolution de novo structure prediction from primary sequence R Wu, F Ding, R Wang, R Shen, X Zhang, S Luo, C Su, Z Wu, Q Xie, ... BioRxiv, 2022.07. 21.500999, 2022 | 393 | 2022 |
Learning Gradient Fields for Molecular Conformation Generation C Shi*, S Luo*, M Xu, J Tang International Conference on Machine Learning (ICML), 2021 | 225 | 2021 |
A 3D Generative Model for Structure-Based Drug Design S Luo, J Guan, J Ma, J Peng Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 217 | 2021 |
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures S Luo, Y Su, X Peng, S Wang, J Peng, J Ma Neural Information Processing Systems (NeurIPS), 2022 | 202 | 2022 |
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 (ICML), 2022 | 182 | 2022 |
Score-Based Point Cloud Denoising S Luo, W Hu International Conference on Computer Vision (ICCV), 2021 | 181 | 2021 |
Learning neural generative dynamics for molecular conformation generation M Xu, S Luo, Y Bengio, J Peng, J Tang International Conference on Learning Representations, 2021 | 134 | 2021 |
Differentiable manifold reconstruction for point cloud denoising S Luo, W Hu Proceedings of the 28th ACM international conference on multimedia, 1330-1338, 2020 | 127 | 2020 |
Deep learning guided optimization of human antibody against SARS-CoV-2 variants with broad neutralization S Shan*, S Luo*, Z Yang*, J Hong*, Y Su, F Ding, L Fu, C Li, P Chen, J Ma, ... Proceedings of the National Academy of Sciences (PNAS) 119 (11), e2122954119, 2022 | 112 | 2022 |
Predicting Molecular Conformation via Dynamic Graph Score Matching S Luo, C Shi, M Xu, J Tang Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 106 | 2021 |
An end-to-end framework for molecular conformation generation via bilevel programming M Xu, W Wang, S Luo, C Shi, Y Bengio, R Gomez-Bombarelli, J Tang International conference on machine learning, 11537-11547, 2021 | 94 | 2021 |
Deep Point Set Resampling via Gradient Fields H Chen, B Du, S Luo, W Hu IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 | 35 | 2022 |
Equivariant Point Cloud Analysis via Learning Orientations for Message Passing S Luo, J Li, J Guan, Y Su, C Cheng, J Peng, J Ma IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 34 | 2022 |
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction S Luo, Y Su, Z Wu, C Su, J Peng, J Ma International Conference on Learning Representations (ICLR), 2023 | 21* | 2023 |
Mutational fitness landscape of human influenza H3N2 neuraminidase R Lei, AH Garcia, TJC Tan, QW Teo, Y Wang, X Zhang, S Luo, SK Nair, ... Cell reports 42 (1), 2023 | 18 | 2023 |
EBM-Fold: fully-differentiable protein folding powered by energy-based models J Wu, S Luo, T Shen, H Lan, S Wang, J Huang arXiv preprint arXiv:2105.04771, 2021 | 10 | 2021 |
Projecting Molecules into Synthesizable Chemical Spaces S Luo, W Gao, Z Wu, J Peng, CW Coley, J Ma International Conference on Machine Learning (ICML), 2024 | 6 | 2024 |
Full-Atom Peptide Design based on Multi-modal Flow Matching J Li, C Cheng, Z Wu, R Guo, S Luo, Z Ren, J Peng, J Ma International Conference on Machine Learning (ICML), 2024 | 6 | 2024 |
Generative Artificial Intelligence for Navigating Synthesizable Chemical Space W Gao, S Luo, CW Coley arXiv preprint arXiv:2410.03494, 2024 | 1 | 2024 |