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The study of Markov processes and broadcasting on trees has deep connections to a variety of areas including statistical physics, graphical models, phylogenetic reconstruction, Markov Chain Monte Carlo, and community detection in random graphs.
Ix. on the problem of the most efficient tests of statistical hypotheses
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Earlier work this paper cites.
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