Sledovat
Ian Char
Název
Citace
Citace
Rok
Beyond pinball loss: Quantile methods for calibrated uncertainty quantification
Y Chung, W Neiswanger, I Char, J Schneider
Advances in Neural Information Processing Systems 34, 10971-10984, 2021
752021
Uncertainty toolbox: an open-source library for assessing, visualizing, and improving uncertainty quantification
Y Chung, I Char, H Guo, J Schneider, W Neiswanger
arXiv preprint arXiv:2109.10254, 2021
752021
Offline Contextual Bayesian Optimization
I Char, Y Chung, W Neiswanger, K Kandasamy, AO Nelson, M Boyer, ...
Advances in Neural Information Processing Systems, 4629-4640, 2019
392019
Neural dynamical systems: Balancing structure and flexibility in physical prediction
V Mehta, I Char, W Neiswanger, Y Chung, A Nelson, M Boyer, E Kolemen, ...
2021 60th IEEE Conference on Decision and Control (CDC), 3735-3742, 2021
26*2021
Toward a non-intrusive, physio-behavioral biometric for smartphones
E Vasiete, Y Chen, I Char, T Yeh, V Patel, L Davis, R Chellappa
Proceedings of the 16th international conference on Human-computer …, 2014
202014
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
192022
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
142023
How useful are gradients for ood detection really?
C Igoe, Y Chung, I Char, J Schneider
arXiv preprint arXiv:2205.10439, 2022
122022
Offline contextual bayesian optimization for nuclear fusion
Y Chung, I Char, W Neiswanger, K Kandasamy, AO Nelson, MD Boyer, ...
arXiv preprint arXiv:2001.01793, 2020
112020
Near-optimal policy identification in active reinforcement learning
X Li, V Mehta, J Kirschner, I Char, W Neiswanger, J Schneider, A Krause, ...
arXiv preprint arXiv:2212.09510, 2022
62022
Bats: Best action trajectory stitching
I Char, V Mehta, A Villaflor, JM Dolan, J Schneider
arXiv preprint arXiv:2204.12026, 2022
62022
A model-based reinforcement learning approach for beta control
I Char, Y Chung, M Boyer, E Kolemen, J Schneider
APS Division of Plasma Physics Meeting Abstracts 2021, PP11. 150, 2021
62021
Exploration via planning for information about the optimal trajectory
V Mehta, I Char, J Abbate, R Conlin, M Boyer, S Ermon, J Schneider, ...
Advances in Neural Information Processing Systems 35, 28761-28775, 2022
52022
Deep attentive variational inference
I Apostolopoulou, I Char, E Rosenfeld, A Dubrawski
International Conference on Learning Representations, 2021
32021
Machine learning for tokamak scenario optimization: combining accelerating physics models and empirical models
M Boyer, J Wai, M Clement, E Kolemen, I Char, Y Chung, W Neiswanger, ...
APS Division of Plasma Physics Meeting Abstracts 2021, PP11. 164, 2021
22021
PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks
I Char, J Schneider
Advances in Neural Information Processing Systems 36, 2024
12024
Towards LLMs as Operational Copilots for Fusion Reactors
V Mehta, J Abbate, A Wang, A Rothstein, I Char, J Schneider, E Kolemen, ...
NeurIPS 2023 AI for Science Workshop, 2023
12023
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, ...
APS Division of Plasma Physics Meeting Abstracts 2022, UP11. 102, 2022
12022
Sample-efficient Plasma Control by Planning for Optimal Trajectory Information
V Mehta, I Char, J Schneider, W Neiswanger, S Ermon, J Abbate, ...
ICML2022 Workshop on Adaptive Experimental Design and Active Learning in the …, 2022
12022
Stochastic Analysis of Minimal Automata Growth for Generalized Strings
IG Char, ME Lladser
Methodology and Computing in Applied Probability, 2019
1*2019
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Články 1–20