[SIPTA] IP graphical models using join/junction/clique trees

Dear all,

I am looking for material on imprecise probabilistic graphical models using using join/junction/clique trees. (Where with 'imprecise probabilistic', I mean to restrict attention to things based on and interpreted as sets of probabilities or gambles, so, e.g., belief functions are out of scope.) Currently, I am aware of

• Van der Gaag's work of ~1990.

• Chrisman's UAI '96 paper "Propagation of 2-monotone lower probabilities on an undirected graph"

• Cano & Moral's 2001 book chapter "Algorithms for imprecise probabilities"

If you are aware of further relevant references, I would be grateful if you could share them with me.

Best regards,

Erik

-- http://users.UGent.be/~equaeghe