We introduce the mixture of Gaussian processes (MGP) model which is useful for applications in which the optimal bandwidth of a map is input dependent. The MGP is derived from the mixture of experts model and can also be used for modeling general conditional probability densities. We discuss how Gaussian processes - in particular in form of Gaussian process classification, the support vector machine and the MGP model--can be used for quantifying the dependencies in graphical models.
['Volker Tresp']
Mixtures of Gaussian Processes