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ORCIDViraj Mehta
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2020 – today
- 2024
[c10]Lucas Spangher, Allen M. Wang, Andrew Maris, Myles Stapelberg, Viraj Mehta, Alex Saperstein, Stephen Lane-Walsh, Akshata Kishore Moharir, Alessandro Pau, Cristina Rea:
Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy. ICML 2024- [i12]Shyam Sundhar Ramesh, Yifan Hu, Iason Chaimalas, Viraj Mehta, Pier Giuseppe Sessa, Haitham Bou-Ammar, Ilija Bogunovic:
Group Robust Preference Optimization in Reward-free RLHF. CoRR abs/2405.20304 (2024) - 2023
- [c9]Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic:
Near-optimal Policy Identification in Active Reinforcement Learning. ICLR 2023 - [c8]Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider:
Offline Model-Based Reinforcement Learning for Tokamak Control. L4DC 2023: 1357-1372 - [i11]Viraj Mehta, Ojash Neopane, Vikramjeet Das, Sen Lin, Jeff Schneider, Willie Neiswanger:
Kernelized Offline Contextual Dueling Bandits. CoRR abs/2307.11288 (2023) - [i10]Viraj Mehta, Vikramjeet Das, Ojash Neopane, Yijia Dai, Ilija Bogunovic, Jeff G. Schneider, Willie Neiswanger:
Sample Efficient Reinforcement Learning from Human Feedback via Active Exploration. CoRR abs/2312.00267 (2023) - 2022
- [c7]Frederic Koehler, Viraj Mehta, Chenghui Zhou, Andrej Risteski:
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias. ICLR 2022 - [c6]Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger:
An Experimental Design Perspective on Model-Based Reinforcement Learning. ICLR 2022 - [c5]Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger:
Exploration via Planning for Information about the Optimal Trajectory. NeurIPS 2022 - [i9]Ian Char, Viraj Mehta, Adam Villaflor, John M. Dolan, Jeff Schneider:
BATS: Best Action Trajectory Stitching. CoRR abs/2204.12026 (2022) - [i8]Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger:
Exploration via Planning for Information about the Optimal Trajectory. CoRR abs/2210.04642 (2022) - [i7]Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic:
Near-optimal Policy Identification in Active Reinforcement Learning. CoRR abs/2212.09510 (2022) - 2021
- [c4]Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson
, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider:
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CDC 2021: 3735-3742 - [c3]Frederic Koehler, Viraj Mehta, Andrej Risteski:
Representational aspects of depth and conditioning in normalizing flows. ICML 2021: 5628-5636 - [i6]Viraj Mehta, Biswajit Paria, Jeff Schneider, Stefano Ermon, Willie Neiswanger:
An Experimental Design Perspective on Model-Based Reinforcement Learning. CoRR abs/2112.05244 (2021) - [i5]Frederic Koehler, Viraj Mehta, Andrej Risteski, Chenghui Zhou:
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias. CoRR abs/2112.06868 (2021) - 2020
- [j1]Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, Silvio Savarese:
Learning task-oriented grasping for tool manipulation from simulated self-supervision. Int. J. Robotics Res. 39(2-3) (2020) - [i4]Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider:
Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction. CoRR abs/2006.12682 (2020) - [i3]Frederic Koehler, Viraj Mehta, Andrej Risteski:
Representational aspects of depth and conditioning in normalizing flows. CoRR abs/2010.01155 (2020)
2010 – 2019
- 2018
- [c2]Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, Silvio Savarese:
Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision. Robotics: Science and Systems 2018 - [c1]Andrey Kurenkov, Jingwei Ji, Animesh Garg, Viraj Mehta, JunYoung Gwak, Christopher B. Choy, Silvio Savarese:
DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image. WACV 2018: 858-866 - [i2]Kuan Fang, Yuke Zhu, Animesh Garg, Andrey Kurenkov, Viraj Mehta, Li Fei-Fei, Silvio Savarese:
Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision. CoRR abs/1806.09266 (2018) - 2017
- [i1]Andrey Kurenkov, Jingwei Ji, Animesh Garg, Viraj Mehta, JunYoung Gwak, Christopher B. Choy, Silvio Savarese:
DeformNet: Free-Form Deformation Network for 3D Shape Reconstruction from a Single Image. CoRR abs/1708.04672 (2017)
Coauthor Index
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