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

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

10 July 2019
J. Kudlicka
Lawrence M. Murray
F. Ronquist
Thomas B. Schon
ArXivPDFHTML

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

4 / 4 papers shown
Title
Nonparametric Hamiltonian Monte Carlo
Nonparametric Hamiltonian Monte Carlo
Carol Mak
Fabian Zaiser
C.-H. Luke Ong
23
6
0
18 Jun 2021
Lazy object copy as a platform for population-based probabilistic
  programming
Lazy object copy as a platform for population-based probabilistic programming
Lawrence M. Murray
16
5
0
09 Jan 2020
Particle filter with rejection control and unbiased estimator of the
  marginal likelihood
Particle filter with rejection control and unbiased estimator of the marginal likelihood
J. Kudlicka
Lawrence M. Murray
Thomas B. Schon
Fredrik Lindsten
11
2
0
21 Oct 2019
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
185
3,262
0
09 Jun 2012
1