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...
| Автори: | , , |
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| Формат: | Стаття |
| Мова: | English |
| Опубліковано: |
Copernicus Publications
2024-10-01
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| Серія: | Advances in Statistical Climatology, Meteorology and Oceanography |
| Онлайн доступ: | https://ascmo.copernicus.org/articles/10/143/2024/ascmo-10-143-2024.pdf |