I would like to know about basics of markov networks (MRFs). Does anyone know an intuitive tutorial about the subject. I just need to very basics information about undirected graphical models.For example how to compute the joint distribution and conditional probabilities of a simple undirected graph(e.g A-B-C)?
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Actually your example is a bit special. In that case I would implement the "Belief Propagation". In general it gives an approximate solution. But in your case it is exact. You can find a, imho, very good tutorial at: https://class.coursera.org/pgm/lecture/49
A complete lecture on Graphical Models is provided in the lecture https://class.coursera.org/pgm/

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