Chemically Interpretable Graph Interaction Network for Prediction of Pharmacokinetic Properties of Drug-Like Molecules. - Yashaswi Pathak; Siddhartha Laghuvarapu; Sarvesh Mehta; U. Deva Priyakumar (AAAI, 2020)

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Simon Blackburn; Karam M. J. Thomas; Connor W. Coley; Jian Tang 005; Sarath Chandar; Yoshua Bengio (ICML, 2020)

Maximum Reward Formulation In Reinforcement Learning. - Sai Krishna Gottipati; Yashaswi Pathak; Rohan Nuttall; Sahir; Raviteja Chunduru; Ahmed Touati; Sriram Ganapathi Subramanian; Matthew E. Taylor; Sarath Chandar (CoRR, 2020)

BAND NN: A Deep Learning Framework for Energy Prediction and Geometry Optimization of Organic Small Molecules. - Siddhartha Laghuvarapu; Yashaswi Pathak; U. Deva Priyakumar (J. Comput. Chem., 2020)

Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery. - Sai Krishna Gottipati; Yashaswi Pathak; Boris Sattarov; Sahir; Rohan Nuttall; Mohammad Amini; Matthew E. Taylor; Sarath Chandar (AAAI, 2021)

Learning Atomic Interactions through Solvation Free Energy Prediction Using Graph Neural Networks. - Yashaswi Pathak; Sarvesh Mehta; U. Deva Priyakumar (J. Chem. Inf. Model., 2021)