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)

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)

MoleGuLAR: Molecule Generation Using Reinforcement Learning with Alternating Rewards. - Manan Goel; Shampa Raghunathan; Siddhartha Laghuvarapu; U. Deva Priyakumar (J. Chem. Inf. Model., 2021)

Benchmark study on deep neural network potentials for small organic molecules. - Rohit Modee; Siddhartha Laghuvarapu; U. Deva Priyakumar (J. Comput. Chem., 2022)

CoDrug: Conformal Drug Property Prediction with Density Estimation under Covariate Shift. - Siddhartha Laghuvarapu; Zhen Lin 001; Jimeng Sun 001 (NeurIPS, 2023)

Molecular De Novo Design through Transformer-based Reinforcement Learning. - Tao Feng; Pengcheng Xu; Tianfan Fu; Siddhartha Laghuvarapu; Jimeng Sun 001 (CoRR, 2023)

Conformal Drug Property Prediction with Density Estimation under Covariate Shift. - Siddhartha Laghuvarapu; Zhen Lin 001; Jimeng Sun 001 (CoRR, 2023)

GraphDDI: Graph Neural Network for Prediction of Drug-Drug Interaction. - Suyash Gupta 003; Siddhartha Laghuvarapu; U. Deva Priyakumar (AIiH (1), 2024)

Vision Language Model is NOT All You Need: Augmentation Strategies for Molecule Language Models. - Namkyeong Lee; Siddhartha Laghuvarapu; Chanyoung Park 001; Jimeng Sun 001 (CIKM, 2024)