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2020 – today
- 2024
[c10]Youngseog Chung, Ian Char, Jeff Schneider:
Sampling-based Multi-dimensional Recalibration. ICML 2024- [i10]Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider:
Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks. CoRR abs/2404.12416 (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 - [c7]Ian Char, Jeff Schneider:
PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks. NeurIPS 2023 - [i9]Ian Char, Jeff G. Schneider:
PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks. CoRR abs/2307.05891 (2023) - 2022
- [c6]Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski:
Deep Attentive Variational Inference. 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 - [i8]Ian Char, Viraj Mehta, Adam Villaflor, John M. Dolan, Jeff Schneider:
BATS: Best Action Trajectory Stitching. CoRR abs/2204.12026 (2022) - [i7]Conor Igoe, Youngseog Chung, Ian Char, Jeff Schneider:
How Useful are Gradients for OOD Detection Really? CoRR abs/2205.10439 (2022) - [i6]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) - [i5]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]Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider:
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. NeurIPS 2021: 10971-10984 - [i4]Youngseog Chung, Ian Char, Han Guo, Jeff Schneider, Willie Neiswanger:
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification. CoRR abs/2109.10254 (2021) - 2020
- [i3]Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider:
Offline Contextual Bayesian Optimization for Nuclear Fusion. CoRR abs/2001.01793 (2020) - [i2]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) - [i1]Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider:
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. CoRR abs/2011.09588 (2020)
2010 – 2019
- 2019
- [c2]Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen:
Offline Contextual Bayesian Optimization. NeurIPS 2019: 4629-4640 - 2014
- [c1]Esther Vasiete, Yan Chen, Ian Char, Tom Yeh, Vishal M. Patel, Larry S. Davis, Rama Chellappa:
Toward a non-intrusive, physio- behavioral biometric for smartphones. Mobile HCI 2014: 501-506
Coauthor Index
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