In the last decade, several architectures have been
proposed for exact computation of marginals using
local computation. In this paper, we compare
Hugin, and Shenoy-Shafer—from the perspective
of graphical structure for message propagation,
message-passing scheme, computational efficiency,
and storage efficiency.
Lepar, V. and P. P. Shenoy, "A Comparison of Lauritzen-Spiegelhalter, Hugin, and Shenoy-Shafer Architectures for Computing Marginals of Probability Distributions," in G. F. Cooper and S. Moral (eds.), Uncertainty in Artificial Intelligence, Vol. 14, 1998, pp. 328--337, Morgan Kaufmann, San Francisco, CA.
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