Nonstationary Gaussian Process Surrogates
Fuente:
arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
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| _version_ | 1866915044824973312 |
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| author | Booth, Annie S. Cooper, Andrew Gramacy, Robert B. |
| author_facet | Booth, Annie S. Cooper, Andrew Gramacy, Robert B. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2305_19242 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Nonstationary Gaussian Process Surrogates Booth, Annie S. Cooper, Andrew Gramacy, Robert B. Methodology 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. |
| title | Nonstationary Gaussian Process Surrogates |
| topic | Methodology |
| url | https://arxiv.org/abs/2305.19242 |