Characterization of Dynamic Bayesian Network
This is an incremental review of DBNs for researchers in probabilistic modeling, with no new contributions.
The report tackles the problem of modeling temporal dimensions with uncertainty by characterizing Dynamic Bayesian Networks (DBNs), focusing on inference and learning concepts and algorithms, but does not present specific results or concrete numbers.
In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and Learning concepts and algorithms. Then we will present different levels and methods of creating DBNs as well as approaches of incorporating temporal dimension in static Bayesian network.