| Chemically interpretable graph interaction network for prediction of pharmacokinetic properties of drug-like molecules Y Pathak, S Laghuvarapu, S Mehta, UD Priyakumar Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 873-880, 2020 | 55 | 2020 |
| Learning atomic interactions through solvation free energy prediction using graph neural networks Y Pathak, S Mehta, UD Priyakumar Journal of Chemical Information and Modeling 61 (2), 689-698, 2021 | 42 | 2021 |
| Memes: Machine learning framework for enhanced molecular screening S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar Chemical science 12 (35), 11710-11721, 2021 | 41 | 2021 |
| 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 | 25 | 2022 |
| PLAS-5k: Dataset of Protein-Ligand Affinities from Molecular Dynamics for Machine Learning Applications DNUDP Divya B. Korlepara, C. S. Vasavi, Shruti Jeurkar, Pradeep Kumar Pal ... Scientific Data 9, 2022 | 19 | 2022 |
| DeepSPInN–deep reinforcement learning for molecular structure prediction from infrared and 13 C NMR spectra S Devata, B Sridharan, S Mehta, Y Pathak, S Laghuvarapu, G Varma, ... Digital Discovery 3 (4), 818-829, 2024 | 10 | 2024 |
| MolOpt: Autonomous Molecular Geometry Optimization Using Multiagent Reinforcement Learning R Modee, S Mehta, S Laghuvarapu, UD Priyakumar The Journal of Physical Chemistry B 127 (48), 10295-10303, 2023 | 6 | 2023 |
| Mo-memes: A method for accelerating virtual screening using multi-objective bayesian optimization S Mehta, M Goel, UD Priyakumar Frontiers in Medicine 9, 916481, 2022 | 4 | 2022 |
| 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, ... | 1 | 2023 |
| Spectra to Structure: Deep Reinforcement Learning for Molecular Inverse Problem B Sridharan, S Mehta, Y Pathak, UD Priyakumar | 1 | 2021 |
| System and method for exploring chemical space during molecular design using a machine learning model UD Priyakumar, S Mehta, S Laghuvarapu, Y Pathak US Patent App. 17/526,712, 2022 | | 2022 |
| VisDrone-DET2020: The Vision Meets Drone Object Detection in Image Challenge Results Computer Vision -- ECCV 2020 Workshops, 692--712, 2020 | | 2020 |
| Supplementary Information for: 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, ... | | |
