Distance-distributed design for Gaussian process surrogates
Abstract
A common challenge in computer experiments and related fields is to efficiently explore the input space using a small number of samples, i.e., the experimental design problem. Much of the recent focus in the computer experiment literature, where modeling is often via Gaussian process (GP) surrogates, has been on space-filling designs, via maximin distance, Latin hypercube, etc. However, it is easy to demonstrate empirically that such designs...
Paper Details
Title
Distance-distributed design for Gaussian process surrogates
Published Date
Dec 6, 2018
Journal
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