15 citations · 17 across the 3 of their papers we have counts for
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stat.CO2021★ 1 cited
The No-U-Turn Sampler as a Proposal Distribution in a Sequential Monte Carlo Sampler with a Near-Optimal L-Kernel
Lee Devlin, Paul Horridge, Peter L. Green +1
Markov Chain Monte Carlo (MCMC) is a powerful method for drawing samples from non-standard probability distributions and is utilized across many fields and disciplines. Methods suc…
stat.CO2020★ 15 cited
Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels
Peter L Green, Robert E Moore, Ryan J Jackson +2
By facilitating the generation of samples from arbitrary probability distributions, Markov Chain Monte Carlo (MCMC) is, arguably, \emph{the} tool for the evaluation of Bayesian inf…