47 citations · 82 across the 11 of their papers we have counts for
4 papers · 1 filter
Active Learning of Piecewise Gaussian Process Surrogates
Chiwoo Park, Robert Waelder, Bonggwon Kang +3
Active learning of Gaussian process (GP) surrogates has been useful for optimizing experimental designs for physical/computer simulation experiments, and for steering data acquisit…
Variable selection for Gaussian process regression through a sparse projection
Chiwoo Park, David J. Borth, Nicholas S. Wilson +1
This paper presents a new variable selection approach integrated with Gaussian process (GP) regression. We consider a sparse projection of input variables and a general stationary…
Robust Gaussian Process Regression with a Bias Model
Chiwoo Park, David J. Borth, Nicholas S. Wilson +2
This paper presents a new approach to a robust Gaussian process (GP) regression. Most existing approaches replace an outlier-prone Gaussian likelihood with a non-Gaussian likelihoo…
Patchwork Kriging for Large-scale Gaussian Process Regression
Chiwoo Park, Daniel Apley
This paper presents a new approach for Gaussian process (GP) regression for large datasets. The approach involves partitioning the regression input domain into multiple local regio…