Approximate Inference for Fully Bayesian Gaussian Process Regression

31 Dec 2019Vidhi LalchandCarl Edward Rasmussen

Learning in Gaussian Process models occurs through the adaptation of hyperparameters of the mean and the covariance function. The classical approach entails maximizing the marginal likelihood yielding fixed point estimates (an approach called \textit{Type II maximum likelihood} or ML-II)... (read more)

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