Char, Ian

11 publications

ICML 2024 Sampling-Based Multi-Dimensional Recalibration Youngseog Chung, Ian Char, Jeff Schneider

NeurIPSW 2023 Correlated Trajectory Uncertainty for Adaptive Sequential Decision Making Ian Char, Youngseog Chung, Rohan Shah, Willie Neiswanger, Jeff Schneider

ICLR 2023 Near-Optimal Policy Identification in Active Reinforcement Learning Xiang Li, Viraj Mehta, Johannes Kirschner, Ian Char, Willie Neiswanger, Jeff Schneider, Andreas Krause, Ilija Bogunovic

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

NeurIPS 2023 PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks Ian Char, Jeff G. Schneider

NeurIPSW 2023 Towards LLMs as Operational Copilots for Fusion Reactors Viraj Mehta, Joseph Abbate, Allen Wang, Andrew Rothstein, Ian Char, Jeff Schneider, Egemen Kolemen, Cristina Rea, Darren Garnier

ICLR 2022 Deep Attentive Variational Inference Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski

NeurIPS 2022 Exploration via Planning for Information About the Optimal Trajectory Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark Boyer, Stefano Ermon, Jeff G. Schneider, Willie Neiswanger

NeurIPS 2021 Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung, Willie Neiswanger, Ian Char, Jeff G. Schneider

ICLRW 2020 Neural Dynamical Systems Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D Boyer, Egemen Kolemen, Jeff Schneider

NeurIPS 2019 Offline Contextual Bayesian Optimization Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark Boyer, Egemen Kolemen, Jeff Schneider