| 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 | 43 | 2020 |
| Band nn: A deep learning framework for energy prediction and geometry optimization of organic small molecules S Laghuvarapu, Y Pathak, UD Priyakumar Journal of computational chemistry 41 (8), 790-799, 2020 | 36 | 2020 |
| Molegular: Molecule generation using reinforcement learning with alternating rewards M Goel, S Raghunathan, S Laghuvarapu, UD Priyakumar Journal of Chemical Information and Modeling 61 (12), 5815-5826, 2021 | 34 | 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 | 34 | 2021 |
| Benchmark study on deep neural network potentials for small organic molecules R Modee, S Laghuvarapu, UD Priyakumar Journal of Computational Chemistry 43 (5), 308-318, 2022 | 3 | 2022 |
| Enhanced Sampling of Chemical Space for High Throughput Screening Applications using Machine Learning S Mehta, S Laghuvarapu, Y Pathak, A Sethi, M Alvala, UD Priyakumar | 3 | 2021 |
| CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift S Laghuvarapu, Z Lin, J Sun Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| 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 |
| DeepSPInN-Deep reinforcement learning for molecular Structure Prediction from Infrared and 13C NMR spectra S Devata, B Sridharan, S Mehta, Y Pathak, S Laghuvarapu, G Varma, ... | | 2024 |
| Streamlining pipeline efficiency: a novel model-agnostic technique for accelerating conditional generative and virtual screening pipelines K Viswanathan, M Goel, S Laghuvarapu, G Varma, UD Priyakumar Scientific Reports 13 (1), 21069, 2023 | | 2023 |
| 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 | | 2023 |
| Conformal Drug Property Prediction with Density Estimation under Covariate Shift S Laghuvarapu, Z Lin, J Sun arXiv preprint arXiv:2310.12033, 2023 | | 2023 |
| Molecular De Novo Design through Transformer-based Reinforcement Learning T Feng, P Xu, T Fu, S Laghuvarapu, J Sun arXiv preprint arXiv:2310.05365, 2023 | | 2023 |
| 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 |
| Deep learning for Prediction of Molecular Properties and Drug Interactions S Laghuvarapu International Institute of Information Technology Hyderabad, 2020 | | 2020 |
| Supplementary Information for MoleGuLaR: Molecule Generation using Reinforcement Learning with Alternating Rewards M Goel, S Raghunathan, S Laghuvarapu, U Deva | | |
U. Deva PriyakumarProfessor, IIIT HyderabadVerified email at iiit.ac.in
