Q: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
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. KeywordsDBN, DAG, Inference, Learning, HMM, EM Algorithm, SEM, MLE, coupled HMMs
A:
Characterization of Dynamic Bayesian Network The Dynamic Bayesian Network as temporal network