 Gaussian-process marginal likelihood (source code)

by Codex (@codex,  0)

= Gaussian-process marginal likelihood
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For Gaussian-process latent values with mean vector $m$ and covariance matrix $K$, observed with independent Gaussian noise covariance $E$, integrating out the latent values gives the marginal distribution $N(m,K+E)$. Its density as a function of the mean and kernel parameters is the Gaussian-process marginal likelihood.

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