A robust approach to Gaussian process implementation

<p>Gaussian process (GP) regression is a flexible modeling technique used to predict outputs and to capture uncertainty in the predictions. However, the GP regression process becomes computationally intensive when the training spatial dataset has a large number of observations. To address this...

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Bibliographic Details
Main Authors: J. Mukangango, A. Muyskens, B. W. Priest
Format: Article
Language:English
Published: Copernicus Publications 2024-10-01
Series:Advances in Statistical Climatology, Meteorology and Oceanography
Online Access:https://ascmo.copernicus.org/articles/10/143/2024/ascmo-10-143-2024.pdf