| PeakVI: A deep generative model for single-cell chromatin accessibility analysis T Ashuach, DA Reidenbach, A Gayoso, N Yosef Cell reports methods 2 (3), 2022 | 69 | 2022 |
| Improving small molecule generation using mutual information machine D Reidenbach, M Livne, RK Ilango, M Gill, J Israeli arXiv preprint arXiv:2208.09016, 2022 | 11 | 2022 |
| Coarsenconf: Equivariant coarsening with aggregated attention for molecular conformer generation D Reidenbach, AS Krishnapriyan Journal of Chemical Information and Modeling, 2024 | 7 | 2024 |
| EvoSBDD: Latent Evolution for Accurate and Efficient Structure-Based Drug Design D Reidenbach ICLR 2024 Workshop on Machine Learning for Genomics Explorations, 2024 | 3 | 2024 |
| BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery PS John, D Lin, P Binder, M Greaves, V Shah, JS John, A Lange, P Hsu, ... arXiv preprint arXiv:2411.10548, 2024 | 1 | 2024 |
| General Binding Affinity Guidance for Diffusion Models in Structure-Based Drug Design Y Jian, C Wu, D Reidenbach, AS Krishnapriyan arXiv preprint arXiv:2406.16821, 2024 | 1 | 2024 |
| Generating multi-step chemical reaction pathways with black-box optimization D Reidenbach, CW Coley, K Yang ICLR 2023-Machine Learning for Drug Discovery workshop, 2023 | 1 | 2023 |
| Targeted Molecular Generation With Latent Reinforcement Learning R Haddad, E Litsa, Z Liu, X Yu, D Burkhardt, D Reidenbach, T Shimko, ... | | 2024 |
| Molecule Generation with Fragment Retrieval Augmentation S Lee, K Kreis, SP Veccham, M Liu, D Reidenbach, S Paliwal, A Vahdat, ... arXiv preprint arXiv:2411.12078, 2024 | | 2024 |
| Generating Optimal Molecules with Synthesizability and 3D Equivariant Conformational Constraints A Krishnapriyan, D Klein | | 2023 |
| Applications of Modular Co-Design for De Novo 3D Molecule Generation D Reidenbach, F Nikitin, O Isayev, SG Paliwal NeurIPS 2024 Workshop on AI for New Drug Modalities, 0 | | |
Aditi KrishnapriyanAssistant Professor, UC Berkeley在 stanford.edu 的电子邮件经过验证
