Adaptive Learning with Gaussian Process Regression: A Comprehensive Review of Methods and Applications
Gaussian processes (GPs) are a popular method in machine learning (ML) to model complex systems. One advantage of GPs over other ML models is their ability to quantify uncertainty in predictions. In the past, many advanced methods for GPs have been developed and published for various applications. A...
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| Päätekijät: | , , |
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| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
MDPI AG
2026-04-01
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| Sarja: | Machine Learning and Knowledge Extraction |
| Aiheet: | |
| Linkit: | https://www.mdpi.com/2504-4990/8/4/101 |
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