Ian Char

According to our database, Ian Char authored at least 15 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Full Shot Predictions for the DIII-D Tokamak via Deep Recurrent Networks.

Ian Char, Youngseog Chung, Joseph Abbate, Egemen Kolemen, Jeff G. Schneider

CoRR, 2024

Sampling-based Multi-dimensional Recalibration.

Youngseog Chung, Ian Char, Jeff Schneider

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

PID-Inspired Inductive Biases for Deep Reinforcement Learning in Partially Observable Control Tasks.

Ian Char, Jeff Schneider

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Offline Model-Based Reinforcement Learning for Tokamak Control.

Ian Char, Joseph Abbate, Laszlo Bardoczi, Mark D. Boyer, Youngseog Chung, Rory Conlin, Keith Erickson, Viraj Mehta, Nathan Richner, Egemen Kolemen, Jeff G. Schneider

Proceedings of the Learning for Dynamics and Control Conference, 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

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

How Useful are Gradients for OOD Detection Really?

Conor Igoe, Youngseog Chung, Ian Char, Jeff Schneider

CoRR, 2022

BATS: Best Action Trajectory Stitching.

Ian Char, Viraj Mehta, Adam Villaflor, John M. Dolan, Jeff Schneider

CoRR, 2022

Exploration via Planning for Information about the Optimal Trajectory.

Viraj Mehta, Ian Char, Joseph Abbate, Rory Conlin, Mark D. Boyer, Stefano Ermon, Jeff Schneider, Willie Neiswanger

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep Attentive Variational Inference.

Ifigeneia Apostolopoulou, Ian Char, Elan Rosenfeld, Artur Dubrawski

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification.

Youngseog Chung, Ian Char, Han Guo, Jeff Schneider, Willie Neiswanger

CoRR, 2021

Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification.

Youngseog Chung, Willie Neiswanger, Ian Char, Jeff Schneider

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Neural Dynamical Systems: Balancing Structure and Flexibility in Physical Prediction.

Viraj Mehta, Ian Char, Willie Neiswanger, Youngseog Chung, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff G. Schneider

Proceedings of the 2021 60th IEEE Conference on Decision and Control (CDC), 2021

2020

Offline Contextual Bayesian Optimization for Nuclear Fusion.

Youngseog Chung, Ian Char, Willie Neiswanger, Kirthevasan Kandasamy, Andrew Oakleigh Nelson, Mark D. Boyer, Egemen Kolemen, Jeff Schneider

CoRR, 2020

2019

Offline Contextual Bayesian Optimization.

Ian Char, Youngseog Chung, Willie Neiswanger, Kirthevasan Kandasamy, Oak Nelson, Mark D. Boyer, Egemen Kolemen

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2014

Toward a non-intrusive, physio- behavioral biometric for smartphones.

Esther Vasiete, Yan Chen, Ian Char, Tom Yeh, Vishal M. Patel, Larry S. Davis, Rama Chellappa

Proceedings of the 16th international conference on Human-computer interaction with mobile devices & services, 2014