32 citations · 182 across the 41 of their papers we have counts for
6 papers · 1 filter
The divide-and-conquer sequential Monte Carlo algorithm: theoretical properties and limit theorems
Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen
We provide a comprehensive characterisation of the theoretical properties of the divide-and-conquer sequential Monte Carlo (DaC-SMC) algorithm. We firmly establish it as a well-fou…
Divide-and-Conquer Fusion
Ryan S. Y. Chan, Murray Pollock, Adam M. Johansen +1
Combining several (sample approximations of) distributions, which we term sub-posteriors, into a single distribution proportional to their product, is a common challenge. Occurring…
Weak Convergence of Non-neutral Genealogies to Kingman's Coalescent
Suzie Brown, Paul A. Jenkins, Adam M. Johansen +1
Interacting particle systems undergoing repeated mutation and selection steps model genetic evolution, and also describe a broad class of sequential Monte Carlo methods. The geneal…
The Node-wise Pseudo-marginal Method
Denishrouf Thesingarajah, Adam M. Johansen
Motivated by problems from neuroimaging in which existing approaches make use of "mass univariate" analysis which neglects spatial structure entirely, but the full joint modelling…
Product-form estimators: exploiting independence to scale up Monte Carlo
Juan Kuntz, Francesca R. Crucinio, Adam M. Johansen
We introduce a class of Monte Carlo estimators that aim to overcome the rapid growth of variance with dimension often observed for standard estimators by exploiting the target's in…
Unbiased simulation of rare events in continuous time
James Hodgson, Adam M. Johansen, Murray Pollock
For rare events described in terms of Markov processes, truly unbiased estimation of the rare event probability generally requires the avoidance of numerical approximations of the…