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# Inference in hybrid Bayesian networks using mixtures of polynomials

@article{Shenoy2011InferenceIH, title={Inference in hybrid Bayesian networks using mixtures of polynomials}, author={Prakash P. Shenoy and James C. West}, journal={Int. J. Approx. Reasoning}, year={2011}, volume={52}, pages={641-657} }

- Published 2011 in Int. J. Approx. Reasoning
DOI:10.1016/j.ijar.2010.09.003

The main goal of this paper is to describe inference in hybrid Bayesian networks (BNs) using mixture of polynomials (MOP) approximations of probability density functions (PDFs). Hybrid BNs contain a mix of discrete, continuous, and conditionally deterministic random variables. The conditionals for continuous variables are typically described by conditional PDFs. A major hurdle in making inference in hybrid BNs is marginalization of continuous variables, which involves integrating combinations… CONTINUE READING

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