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Survey of Bayesian Models for Modelling of Stochastic Temporal Processes
Author(s) -
Ben Ng
Publication year - 2006
Language(s) - English
Resource type - Reports
DOI - 10.2172/900168
Subject(s) - dynamic bayesian network , computer science , bayesian network , representation (politics) , bayesian probability , probabilistic logic , variable order bayesian network , generative grammar , generative model , artificial intelligence , bayesian inference , machine learning , data mining , politics , political science , law
This survey gives an overview of popular generative models used in the modeling of stochastic temporal systems. In particular, this survey is organized into two parts. The first part discusses the discrete-time representations of dynamic Bayesian networks and dynamic relational probabilistic models, while the second part discusses the continuous-time representation of continuous-time Bayesian networks

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