Hi! I am a third year PhD student in Machine Learning at Carnegie Mellon University, fortunate to be advised by Zachary Lipton and Bryan Wilder. Previously, I received my BS in Physics and BA in Computer Science from Brown University in 2021.

preprints

Decision-Focused Uncertainty Quantification
Santiago Cortes-Gomez, Carlos Patiño, Yewon Byun, Steven Wu, Eric Horvitz, Bryan Wilder
Preprint.
[arXiv] [code]

The Value of Synthetic Data in Expert Routing for Continual Learning
Yewon Byun, Sanket V. Mehta, Saurabh Garg, Emma Strubell, Bryan Wilder, Zachary Lipton
Preprint.
[arXiv] [code]

publications

Decision-Focused Evaluation of Worst-Case Distribution Shift
Kevin Ren, Yewon Byun, Bryan Wilder
Uncertainty in Artificial Intelligence (UAI), 2024.
[arXiv] [code]

Auditing Fairness under Unobserved Confounding
Yewon Byun, Dylan Sam, Michael Oberst, Zachary Lipton, Bryan Wilder
International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
[arXiv] [code]

Domain Knowledge Priors for Bayesian Neural Networks
Dylan Sam*, Rattana Pukdee*, Daniel Jeong, Yewon Byun, Zico Kolter
International Conference on Machine Learning (ICML) Knowledge and Logical Reasoning, 2023. (Oral)
[arXiv] [code]

contact: yewonb@cs.cmu.edu
twitter: @yewonbyun_

last updated April 14, 2024