| Modern machine learning for tackling inverse problems in chemistry: molecular design to realization B Sridharan, M Goel, UD Priyakumar Chemical Communications 58 (35), 5316-5331, 2022 | 41 | 2022 |
| Deep Reinforcement Learning for Molecular Inverse Problem of Nuclear Magnetic Resonance Spectra to Molecular Structure B Sridharan, S Mehta, Y Pathak, UD Priyakumar The Journal of Physical Chemistry Letters 13 (22), 4924-4933, 2022 | 26 | 2022 |
| Plas-5k: Dataset of protein-ligand affinities from molecular dynamics for machine learning applications DB Korlepara, CS Vasavi, S Jeurkar, PK Pal, S Roy, S Mehta, S Sharma, ... Scientific Data 9 (1), 548, 2022 | 19 | 2022 |
| Efficient and enhanced sampling of drug‐like chemical space for virtual screening and molecular design using modern machine learning methods M Goel, R Aggarwal, B Sridharan, PK Pal, UD Priyakumar Wiley Interdisciplinary Reviews: Computational Molecular Science 13 (2), e1637, 2023 | 18 | 2023 |
| DeepSPInN-multimodal Deep learning for molecular Structure Prediction from Infrared and NMR spectra S Devata, B Sridharan, S Mehta, Y Pathak, S Laghuvarapu, G Varma, ... | 11* | 2023 |
| Deep reinforcement learning in chemistry: A review B Sridharan, A Sinha, J Bardhan, R Modee, M Ehara, UD Priyakumar Journal of Computational Chemistry, 2024 | 5 | 2024 |
| Spectra to Structure: Contrastive Learning Framework for Library Ranking and Generating Molecular Structures for Infrared Spectra GC Kanakala, B Sridharan, UD Priyakumar Digital Discovery, 2024 | | 2024 |
U. Deva PriyakumarProfessor, IIIT HyderabadAdresse e-mail validée de iiit.ac.in
