Group Kernels for Gaussian Process Metamodels with Categorical Inputs Article Swipe
Olivier Roustant
,
Espéran Padonou
,
Yves Deville
,
Aloïs Clément
,
Guillaume Perrin
,
J. Giorla
,
Henry P. Wynn
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1137/18m1209386
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1137/18m1209386
Gaussian processes (GP) are widely used as a metamodel for emulating time-consuming computer codes. We focus on problems involving categorical inputs, with a potentially large number L of levels (typically several tens), partitioned in G << L groups of various sizes. Parsimonious covariance functions, or kernels, can then be defined by block covariance matrices T with constant covariances between pairs of blocks and within blocks. We study the positive definiteness of such matrices to encourage their practical use. The hierarchical group/level structure, equivalent to a nested Bayesian linear model, provides a parameterization of valid block matrices T. The same model can then be used when the assumption within blocks is relaxed, giving a flexible parametric family of valid covariance matrices with constant covariances between pairs of blocks. The positive definiteness of T is equivalent to the positive definiteness of a smaller matrix of size G, obtained by averaging each block. The model is applied to a problem in nuclear waste analysis, where one of the categorical inputs is atomic number, which has more than 90 levels.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1137/18m1209386
- OA Status
- green
- Cited By
- 7
- References
- 21
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W2787306014Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1137/18m1209386Digital Object Identifier
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Group Kernels for Gaussian Process Metamodels with Categorical InputsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-01-01Full publication date if available
- Authors
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Olivier Roustant, Espéran Padonou, Yves Deville, Aloïs Clément, Guillaume Perrin, J. Giorla, Henry P. WynnList of authors in order
- Landing page
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https://doi.org/10.1137/18m1209386Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/1802.02368Direct OA link when available
- Concepts
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Categorical variable, Group (periodic table), Gaussian process, Process (computing), Kriging, Computer science, Gaussian, Mathematics, Artificial intelligence, Statistics, Physics, Quantum mechanics, Operating systemTop concepts (fields/topics) attached by OpenAlex
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7Total citation count in OpenAlex
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2024: 2, 2023: 1, 2021: 2, 2020: 1, 2019: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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