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- W114616615 abstract "Abstract In this article, a new mechanism is described for modeling and evaluating Hybrid Dynamic Bayesian networks. The approach uses Gaussian mixtures and Dirac mixtures as messages to calculate marginal densities. As these densities are approximated by means of Gaussian mixtures, any desired precision is possible. The presented approach removes the restrictions of sample based evaluation of Bayesian networks since it uses an analytical approximation scheme for probability densities which systematically minimizes the distance between the exact and the approximate density." @default.
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- W114616615 date "2005-01-01" @default.
- W114616615 modified "2023-09-25" @default.
- W114616615 title "EVALUATION OF HYBRID BAYESIAN NETWORKS USING ANALYTICAL DENSITY REPRESENTATIONS" @default.
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- W114616615 doi "https://doi.org/10.3182/20050703-6-cz-1902.00381" @default.
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