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This type of graphical model is known as a directed graphical model, [[Bayesian network]], or belief network.
There are also undirected graphical models, also called [[Markov network|Markov networks]], in which graph separation encodes conditional independencies (these are also known as graphical Gaussian models, or GGMs).
A recent application of graphical models is to describe [[gene regulatory network]]s.
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