Cargando…
Automated Model Inference for Gaussian Processes: An Overview of State-of-the-Art Methods and Algorithms
Gaussian process models (GPMs) are widely regarded as a prominent tool for learning statistical data models that enable interpolation, regression, and classification. These models are typically instantiated by a Gaussian Process with a zero-mean function and a radial basis covariance function. While...
| Autores principales: | , , |
|---|---|
| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Nature Singapore
2022
|
| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9123926/ https://www.ncbi.nlm.nih.gov/pubmed/35647556 http://dx.doi.org/10.1007/s42979-022-01186-x |