Probabilistic programming for birth-death models of evolution using an alive particle filter with delayed sampling

10 Jul 2019Jan KudlickaLawrence M. MurrayFredrik RonquistThomas B. Schön

We consider probabilistic programming for birth-death models of evolution and introduce a new widely-applicable inference method that combines an extension of the alive particle filter (APF) with automatic Rao-Blackwellization via delayed sampling. Birth-death models of evolution are an important family of phylogenetic models of the diversification processes that lead to evolutionary trees... (read more)

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