Gaussian Processes for Machine Learning¶
Rasmussen, C. E., & Williams, C. K. I. (2006). Gaussian Processes for Machine Learning. MIT Press.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Domain-specific¶
- Kriging
- Without Gaussianity, kriging retains its best-linear-unbiased interpretation but not a full posterior-distribution equivalence.
This sourceAuthoritative reference for Gaussian-process priors, covariance functions, observation-noise models, conditioning, posterior means, and posterior variances.
- Without Gaussianity, kriging retains its best-linear-unbiased interpretation but not a full posterior-distribution equivalence.
Verification¶
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Registry ID ref:71605e257e04 · see in the full table