Abstract
Probabilistic reasoning can be modeled through the use of graphs — the vertices in the graphs represent random variables, while the edges represent dependencies between the random variables. Such representations play a fundamental role in the development of expert systems, in part because they allow for a rapid factorization and evaluation of the joint probability distributions of the graph variables [CGH97].
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Heegard, C., Wicker, S.B. (1999). Belief Propagation and Parallel Decoding. In: Turbo Coding. The Springer International Series in Engineering and Computer Science, vol 476. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-2999-3_7
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DOI: https://doi.org/10.1007/978-1-4757-2999-3_7
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