DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image. - Andrey Kurenkov; Jingwei Ji; Animesh Garg; Viraj Mehta; JunYoung Gwak; Christopher B. Choy; Silvio Savarese (WACV, 2018)

Learning task-oriented grasping for tool manipulation from simulated self-supervision. - Kuan Fang; Yuke Zhu; Animesh Garg; Andrey Kurenkov; Viraj Mehta; Li Fei-Fei 001; Silvio Savarese (Int. J. Robotics Res., 2020)

Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. - Viraj Mehta; Ian Char; Willie Neiswanger; Youngseog Chung; Andrew Oakleigh Nelson; Mark D. Boyer; Egemen Kolemen; Jeff G. Schneider (CDC, 2021)

Representational aspects of depth and conditioning in normalizing flows. - Frederic Koehler; Viraj Mehta; Andrej Risteski (ICML, 2021)

Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias. - Frederic Koehler; Viraj Mehta; Chenghui Zhou; Andrej Risteski (ICLR, 2022)

An Experimental Design Perspective on Model-Based Reinforcement Learning. - Viraj Mehta; Biswajit Paria; Jeff Schneider 001; Stefano Ermon; Willie Neiswanger (ICLR, 2022)

Exploration via Planning for Information about the Optimal Trajectory. - Viraj Mehta; Ian Char; Joseph Abbate; Rory Conlin; Mark D. Boyer; Stefano Ermon; Jeff Schneider 001; Willie Neiswanger (NeurIPS, 2022)

BATS: Best Action Trajectory Stitching. - Ian Char; Viraj Mehta; Adam Villaflor; John M. Dolan; Jeff Schneider 001 (CoRR, 2022)

Near-optimal Policy Identification in Active Reinforcement Learning. - Xiang Li; Viraj Mehta; Johannes Kirschner; Ian Char; Willie Neiswanger; Jeff Schneider 001; Andreas Krause 001; Ilija Bogunovic (ICLR, 2023)

Offline Model-Based Reinforcement Learning for Tokamak Control. - Ian Char; Joseph Abbate; Laszlo Bardoczi; Mark D. Boyer; Youngseog Chung; Rory Conlin; Keith Erickson; Viraj Mehta; Nathan Richner; Egemen Kolemen; Jeff G. Schneider (L4DC, 2023)

Kernelized Offline Contextual Dueling Bandits. - Viraj Mehta; Ojash Neopane; Vikramjeet Das; Sen Lin; Jeff Schneider 001; Willie Neiswanger (CoRR, 2023)

Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration. - Viraj Mehta; Vikramjeet Das; Ojash Neopane; Yijia Dai; Ilija Bogunovic; Jeff G. Schneider; Willie Neiswanger (CoRR, 2023)

Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy. - Lucas Spangher; Allen M. Wang; Andrew Maris; Myles Stapelberg; Viraj Mehta; Alex Saperstein; Stephen Lane-Walsh; Akshata Kishore Moharir; Alessandro Pau; Cristina Rea (ICML, 2024)

Group Robust Preference Optimization in Reward-free RLHF. - Shyam Sundhar Ramesh; Yifan Hu; Iason Chaimalas; Viraj Mehta; Pier Giuseppe Sessa; Haitham Bou-Ammar; Ilija Bogunovic (NeurIPS, 2024)

Sample-Efficient Reinforcement Learning with Applications in Nuclear Fusion - Viraj Mehta (2024)