Personal tools
You are here: Home Publications Mixtures of Gaussian Processes
Document Actions

Volker Tresp (2001)

Mixtures of Gaussian Processes

In: Advances in Neural Information Processing Systems, vol. 13.

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.

by admin last modified 2007-01-31 11:09

Powered by Plone CMS, the Open Source Content Management System