41 citations · 53 across the 4 of their papers we have counts for
4 papers
Beyond Parameter Count: Implicit Bias in Soft Mixture of Experts
Youngseog Chung, Dhruv Malik, Jeff Schneider +2
The traditional viewpoint on Sparse Mixture of Experts (MoE) models is that instead of training a single large expert, which is computationally expensive, we can train many small e…
How Useful are Gradients for OOD Detection Really?
Conor Igoe, Youngseog Chung, Ian Char +1
One critical challenge in deploying highly performant machine learning models in real-life applications is out of distribution (OOD) detection. Given a predictive model which is ac…
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification
Youngseog Chung, Ian Char, Han Guo +2
With increasing deployment of machine learning systems in various real-world tasks, there is a greater need for accurate quantification of predictive uncertainty. While the common…
Offline Contextual Bayesian Optimization for Nuclear Fusion
Youngseog Chung, Ian Char, Willie Neiswanger +5
Nuclear fusion is regarded as the energy of the future since it presents the possibility of unlimited clean energy. One obstacle in utilizing fusion as a feasible energy source is…