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Line 21: Applications of graphical models include modelling of [[gene regulatory network]]s, [[speech recognition]], gene finding, [[computer vision]] and diagnosis of diseases. A good reference for learning the basics of graphical models is written by Neapolitan, Learning Bayesian networks (2004). A more advanced and statistically oriented book is by Cowell, Dawid, Lauritzen and Spiegelhalter, Probabilistic networks and expert systems (1999). ==See also== *[[belief propagation]]. ==Reference==

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