2017
Prediction Performance After Learning in Gaussian Process Regression
AISTATS 2017poster
This paper considers the quantification of the prediction performance in Gaussian process regression. The standard approach is to base the prediction error bars on the theoretical predictive variance, which is a lower bound on the mean square-error (MSE). This approach, however, does not take into a…