A Bayesian network (also known as a Bayes network, Bayes net, belief network, or decision network) is a probabilistic graphical model that represents...

dynamic Bayesian network (DBN) is a Bayesian network (BN) which relates variables to each other over adjacent time steps. A dynamic Bayesian network (DBN)...

learning. Bayesian networks that model sequences of variables, like speech signals or protein sequences, are called dynamic Bayesian networks. Generalizations...

the classifier its name. These classifiers are among the simplest Bayesian network models. Naive Bayes classifiers are highly scalable, requiring a number...

Bayesian statistics (/ˈbeɪziən/ BAY-zee-ən or /ˈbeɪʒən/ BAY-zhən) is a theory in the field of statistics based on the Bayesian interpretation of probability...

dynamic decision networks, game theory and mechanism design. Bayesian networks are a tool that can be used for reasoning (using the Bayesian inference algorithm)...

a fallback Dynamic Bayesian network – Probabilistic graphical model International Society for Bayesian Analysis Perfect Bayesian equilibrium – Solution...

A Markov network or MRF is similar to a Bayesian network in its representation of dependencies; the differences being that Bayesian networks are directed...

decision network) is a compact graphical and mathematical representation of a decision situation. It is a generalization of a Bayesian network, in which...

Markov blanket. The Markov boundary of a node A {\displaystyle A} in a Bayesian network is the set of nodes composed of A {\displaystyle A} 's parents, A {\displaystyle...