Allan,

in the following paper we describe learning the 
structure of a Bayesian Network from a dataset 
with nonlinear relationships between continuous 
variables. The Bayesian Network uses kernel-based 
estimators to model those nonlinear relationships:

   "Discovering Structure in Continuous Variables using 
    Bayesian Networks"
    Reimar Hofmann and Volker Tresp 
    NIPS*95
   
(http://wwwbrauer.informatik.tu-muenchen.de/~hofmannr/nips95_abstr.html)

In a second paper we describe structure learning in 
Markov Networks for nonlinear relationships 
between continuous variables:

   "Nonlinear Markov Networks for Continuous Variables"
    Reimar Hofmann and Volker Tresp
    NIPS*97
   
(http://wwwbrauer.informatik.tu-muenchen.de/~hofmannr/nips97_abstr.html)

Best regards,

Reimar

-- 
___________________________________________________________________________
Reimar Hofmann      
ZT IK 4              www:  
http://www7.informatik.tu-muenchen.de/~hofmannr
Siemens AG, CR & D   Email: [EMAIL PROTECTED]
81730 Muenchen       Tel:   +49/89/636-50804
Germany              Fax:   +49/89/636-49767

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