Nonstationary Gaussian Process Surrogates
Methodology
2024-12-04 v2
Abstract
We provide a survey of nonstationary surrogate models which utilize Gaussian processes (GPs) or variations thereof, including nonstationary kernel adaptations, partition and local GPs, and spatial warpings through deep Gaussian processes. We also overview publicly available software implementations and conclude with a bake-off involving an 8-dimensional satellite drag computer experiment. Code for this example is provided in a public git repository.
Keywords
Cite
@article{arxiv.2305.19242,
title = {Nonstationary Gaussian Process Surrogates},
author = {Annie S. Booth and Andrew Cooper and Robert B. Gramacy},
journal= {arXiv preprint arXiv:2305.19242},
year = {2024}
}
Comments
13 pages, 5 figures