Viraj Mehta
Viraj Mehta
Verified email at - Homepage
Cited by
Cited by
Learning Task-Oriented Grasping for Tool Manipulation from Simulated Self-Supervision
K Fang, Y Zhu, A Garg, A Kurenkov, V Mehta, L Fei-Fei, S Savarese
The International Journal of Robotics Research, 2018
Deformnet: Free-form deformation network for 3d shape reconstruction from a single image
A Kurenkov, J Ji, A Garg, V Mehta, JY Gwak, C Choy, S Savarese
2018 IEEE Winter Conference on Applications of Computer Vision (WACV), 858-866, 2018
Neural dynamical systems: Balancing structure and flexibility in physical prediction
V Mehta, I Char, W Neiswanger, Y Chung, AO Nelson, MD Boyer, ...
2021 60th IEEE Conference on Decision and Control (CDC), 2021
Representational aspects of depth and conditioning in normalizing flows
F Koehler, V Mehta, A Risteski
International Conference on Machine Learning, 5628-5636, 2021
DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy
ME Fenstermacher, J Abbate, S Abe, T Abrams, M Adams, B Adamson, ...
Nuclear Fusion 62 (4), 042024, 2022
An Experimental Design Perspective on Model-Based Reinforcement Learning
V Mehta, B Paria, J Schneider, S Ermon, W Neiswanger
International Conference on Learning Representations, 2022
Effects of chemical inhibitors and apyrase enzyme further document a role for apyrases and extracellular ATP in the opening and closing of stomates in Arabidopsis
G Clark, C Darwin, V Mehta, F Jackobs, T Perry, K Hougaard, S Roux
Plant signaling & behavior 8 (11), e26093, 2013
Variational autoencoders in the presence of low-dimensional data: landscape and implicit bias
F Koehler, V Mehta, A Risteski, C Zhou
International Conference on Learning Representations, 2022
BATS: Best Action Trajectory Stitching
I Char, V Mehta, A Villaflor, JM Dolan, J Schneider
Offline Reinforcement Learning Workshop at Neural Information Processing Systems, 2022
Near-optimal Policy Identification in Active Reinforcement Learning
X Li, V Mehta, J Kirschner, I Char, W Neiswanger, J Schneider, A Krause, ...
International Conference on Learning Representations, 2023
Offline Model-Based Reinforcement Learning for Tokamak Control
I Char, J Abbate, L Bardóczi, M Boyer, Y Chung, R Conlin, K Erickson, ...
Learning for Dynamics and Control Conference, 1357-1372, 2023
Exploration via Planning for Information about the Optimal Trajectory
V Mehta, I Char, J Abbate, R Conlin, MD Boyer, S Ermon, J Schneider, ...
Advances in Neural Information Processing Systems 36, 2022
Sample-efficient Plasma Control by Planning for Optimal Trajectory Information
V Mehta, I Char, J Schneider, W Neiswanger, S Ermon, J Abbate, ...
ICML Workshop on Adaptive Experimental Design and Active Learning in the …, 2022
Finding Your Way, Courtesy of Machine Learning
C Asawa, M Gomez, V Mehta
Stanford CS, 2016
Kernelized Offline Contextual Dueling Bandits
V Mehta, O Neopane, V Das, S Lin, J Schneider, W Neiswanger
arXiv preprint arXiv:2307.11288, 2023
Differential Rotation Control for the DIII-D Tokamak via Model-Based Reinforcement Learning
I Char, J Abbate, V Mehta, Y Chung, R Conlin, K Erickson, M Boyer, ...
Bulletin of the American Physical Society, 2022
Controlling Plasma Profiles in a Learned Model via Reinforcement Learning
V Mehta, J Abbate, R Conlin, E Kolemen, J Schneider
APS Division of Plasma Physics Meeting Abstracts 2021, GP11. 037, 2021
Juxtaposing Deep Learning Architectures for Breast Cancer Classification
P Raut, V Mehta, A Kadakia
Advanced Computing Technologies and Applications: Proceedings of 2nd …, 2020
Towards Grasp Transfer using Shape Deformation
A Kurenkov, V Mehta, J Ji, A Garg, S Savarese
Conference on Robot Learning (short paper), 2017
The system can't perform the operation now. Try again later.
Articles 1–19