Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Efficient Bayesian Inference Framework for Coalescent-Based
  Nonparametric Phylodynamics   Phylodynamics focuses on the problem of reconstructing past population size
dynamics from current genetic samples taken from the population of interest.
This technique has been extensively used in many areas of biology, but is
particularly useful for studying the spread of quickly evolving infectious
diseases agents, e.g.,\ influenza virus. Phylodynamics inference uses a
coalescent model that defines a probability density for the genealogy of
randomly sampled individuals from the population. When we assume that such a
genealogy is known, the coalescent model, equipped with a Gaussian process
prior on population size trajectory, allows for nonparametric Bayesian
estimation of population size dynamics. While this approach is quite powerful,
large data sets collected during infectious disease surveillance challenge the
state-of-the-art of Bayesian phylodynamics and demand computationally more
efficient inference framework. To satisfy this demand, we provide a
computationally efficient Bayesian inference framework based on Hamiltonian
Monte Carlo for coalescent process models. Moreover, we show that by splitting
the Hamiltonian function we can further improve the efficiency of this
approach. Using several simulated and real datasets, we show that our method
provides accurate estimates of population size dynamics and is substantially
faster than alternative methods based on elliptical slice sampler and
Metropolis-adjusted Langevin algorithm.

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The categories of this paper are: mtrl-th
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The categories of this paper are: nucl-th
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The categories of this paper are: chao-dyn
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The categories of this paper are: solv-int
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The categories of this paper are: funct-an
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The categories of this paper are: quant-ph
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The categories of this paper are: q-fin
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The categories of this paper are: bayes-an
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The categories of this paper are: gr-qc
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The categories of this paper are: cmp-lg
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The categories of this paper are: dg-ga
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The categories of this paper are: hep-th
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The categories of this paper are: ao-sci
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The categories of this paper are: math
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The categories of this paper are: q-bio
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The categories of this paper are: astro-ph