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Yashaswi Pathak
Yashaswi Pathak
Undergraduate Researcher, IIIT Hyderabad
Verified email at research.iiit.ac.in - Homepage
Title
Cited by
Cited by
Year
Learning to navigate the synthetically accessible chemical space using reinforcement learning
SK Gottipati, B Sattarov, S Niu, Y Pathak, H Wei, S Liu, S Blackburn, ...
International conference on machine learning, 3668-3679, 2020
1162020
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
422020
Deep learning enabled inorganic material generator
Y Pathak, KS Juneja, G Varma, M Ehara, UD Priyakumar
Physical Chemistry Chemical Physics 22 (46), 26935-26943, 2020
412020
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
352020
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
332021
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
272021
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
122022
Maximum reward formulation in reinforcement learning
SK Gottipati, Y Pathak, R Nuttall, R Chunduru, A Touati, SG Subramanian, ...
arXiv preprint arXiv:2010.03744, 2020
72020
Towered actor critic for handling multiple action types in reinforcement learning for drug discovery
SK Gottipati, Y Pathak, B Sattarov, R Nuttall, M Amini, ME Taylor, ...
Proceedings of the AAAI Conference on Artificial Intelligence 35 (1), 142-150, 2021
62021
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
32021
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, ...
12023
Maximum reward formulation in reinforcement learning
S Krishna Gottipati, Y Pathak, R Nuttall, R Chunduru, A Touati, ...
arXiv e-prints, arXiv: 2010.03744, 2020
12020
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
System and method for learning to generate chemical compounds with desired properties
B Sattarov, VSK Gottipati, Y Pathak, K Thomas
US Patent App. 17/796,826, 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
Spectra to Structure: Deep Reinforcement Learning for Molecular Inverse Problem
B Sridharan, S Mehta, Y Pathak, UD Priyakumar
2021
MAXIMUM REWARD FORMULATION IN REINFORCE-MENT LEARNING
SGS Touati, ME Taylor, S Chandar
SUPPLEMENTARY MATERIAL-LEARNING TO NAVIGATE THE SYNTHETICALLY ACCESSIBLE CHEMICAL SPACE USING REINFORCEMENT LEARNING
SK Gottipati, B Sattarov, S Niu10, Y Pathak, H Wei, S Liu, KJ Thomas, ...
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