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Spatial mapping with Gaussian processes and nonstationary Fourier features
The use of covariance kernels is ubiquitous in the field of spatial statistics. Kernels allow data to be mapped into high-dimensional feature spaces and can thus extend simple linear additive methods to nonlinear methods with higher order interactions. However, until recently, there has been a stron...
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| Udgivet i: | Spat Stat |
|---|---|
| Main Authors: | , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
Elsevier B.V
2018
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6472673/ https://ncbi.nlm.nih.gov/pubmed/31008043 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.spasta.2018.02.002 |
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