Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels

A Gaussian Process (GP) is a prominent mathematical framework for stochastic function approximation in science and engineering applications. Its success is largely attributed to the GP’s analytical tractability, robustness, and natural inclusion of uncertainty quantification. Unfortunately, the use...

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Detalles Bibliográficos
Autores principales: Noack, Marcus M., Krishnan, Harinarayan, Risser, Mark D., Reyes, Kristofer G.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011418/
https://www.ncbi.nlm.nih.gov/pubmed/36914705
http://dx.doi.org/10.1038/s41598-023-30062-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10011418/
https://www.ncbi.nlm.nih.gov/pubmed/36914705
http://dx.doi.org/10.1038/s41598-023-30062-8

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