Ueber die Normirung der Borchardt'schen Moduln der hyperelliptischen Functionen vom Geschlechte p = 2
Given a fixed dependency graph that describes a Bayesian network of binary variables , our main result is a tight bound on the mutual information of an observed subset of the variables . Our bound depends on certain quantities that can be computed from the connective structure of the nodes in . Thus it allows to discriminate between different dependency graphs for a probability distribution, as we show from numerical experiments.
Page 1