1. A system for analyzing and synthesizing data from a plurality of sources of sample data by Gaussian process learning and regression, the system comprising: data storage with a stored multi-task covariance function and associated hyperparameters, and an evaluation processor in communication with the data storage that: performs Gaussian process regression using the stored sample data and multi-task covariance function with the hyperparameters and synthesizes prediction data for use in graphical display or digital control, wherein the multi-task covariance function is a combination of a plurality of stationary covariance functions.