In this paper we introduced the notion of Gaussian Process
networks and developed the Bayesian score for learning
these. We report on preliminary results that show that
this method generalizes well from noisy data. The combination
of this powerful regression technique with the flexible
language of Bayesian networks seems like a promising
tool for exploratory data analysis, causal structure discovery,
prediction, and Bayesian classification.