Offline Contextual Bayesian Optimization. - Ian Char; Youngseog Chung; Willie Neiswanger; Kirthevasan Kandasamy; Oak Nelson; Mark D. Boyer; Egemen Kolemen (NeurIPS, 2019)

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 001 (CoRR, 2020)

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 (CDC, 2021)

Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification. - Youngseog Chung; Willie Neiswanger; Ian Char; Jeff Schneider 001 (NeurIPS, 2021)

Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification. - Youngseog Chung; Ian Char; Han Guo; Jeff Schneider 001; Willie Neiswanger (CoRR, 2021)

How Useful are Gradients for OOD Detection Really? - Conor Igoe; Youngseog Chung; Ian Char; Jeff Schneider 001 (CoRR, 2022)

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 (L4DC, 2023)

Parity calibration. - Youngseog Chung; Aaron Rumack; Chirag Gupta (UAI, 2023)

Bi-Manual Block Assembly via Sim-to-Real Reinforcement Learning. - Satoshi Kataoka; Youngseog Chung; Seyed Kamyar Seyed Ghasemipour; Pannag Sanketi; Shixiang Shane Gu; Igor Mordatch (CoRR, 2023)

MUDD: A New Re-Identification Dataset with Efficient Annotation for Off-Road Racers in Extreme Conditions. - Jacob Tyo; Motolani Olarinre; Youngseog Chung; Zachary C. Lipton (CoRR, 2023)

Reading Between the Mud: A Challenging Motorcycle Racer Number Dataset. - Jacob Tyo; Youngseog Chung; Motolani Olarinre; Zachary C. Lipton (CoRR, 2023)

Sampling-based Multi-dimensional Recalibration. - Youngseog Chung; Ian Char; Jeff Schneider 001 (ICML, 2024)

Beyond the Mud: Datasets and Benchmarks for Computer Vision in Off-Road Racing. - Jacob Tyo; Motolani Olarinre; Youngseog Chung; Zachary C. Lipton (CoRR, 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)

What is Your Data Worth to GPT? LLM-Scale Data Valuation with Influence Functions. - Sang Keun Choe; Hwijeen Ahn; Juhan Bae; Kewen Zhao; Minsoo Kang; Youngseog Chung; Adithya Pratapa; Willie Neiswanger; Emma Strubell; Teruko Mitamura; Jeff G. Schneider; Eduard H. Hovy; et al. (CoRR, 2024)

Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts. - Youngseog Chung; Dhruv Malik; Jeff Schneider 001; Yuanzhi Li; Aarti Singh (Trans. Mach. Learn. Res., 2025)