Abstract
This paper proposes a flexible framework to work with probabilistic potentials in Probabilistic Graphical Models. The so-called Extended Probability Trees allow the representation of multiplicative and additive factorisations within the structure, along with context-specific independencies, with the aim of providing a way of representing and managing complex distributions. This work gives the details of the structure and develops the basic operations on potentials necessary to perform inference. The three basic operations, namely restriction, combination and marginalisation, are defined so they can take advantage of the defined factorisations within the structure, following a lazy methodology.
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Cano, A., Gómez-Olmedo, M., Moral, S., Pérez-Ariza, C.B. (2014). Extended Probability Trees for Probabilistic Graphical Models. In: van der Gaag, L.C., Feelders, A.J. (eds) Probabilistic Graphical Models. PGM 2014. Lecture Notes in Computer Science(), vol 8754. Springer, Cham. https://doi.org/10.1007/978-3-319-11433-0_8
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DOI: https://doi.org/10.1007/978-3-319-11433-0_8
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