18 citations · 47 across the 16 of their papers we have counts for
4 papers · 1 filter
Conditional sequential Monte Carlo in high dimensions
Axel Finke, Alexandre H. Thiery
The iterated conditional sequential Monte Carlo (i-CSMC) algorithm from Andrieu, Doucet and Holenstein (2010) is an MCMC approach for efficiently sampling from the joint posterior…
Limit theorems for sequential MCMC methods
Axel Finke, Arnaud Doucet, Adam M. Johansen
Sequential Monte Carlo (SMC) methods, also known as particle filters, constitute a class of algorithms used to approximate expectations with respect to a sequence of probability di…
On embedded hidden Markov models and particle Markov chain Monte Carlo methods
Axel Finke, Arnaud Doucet, Adam M. Johansen
The embedded hidden Markov model (EHMM) sampling method is a Markov chain Monte Carlo (MCMC) technique for state inference in non-linear non-Gaussian state-space models which was p…
Approximate Smoothing and Parameter Estimation in High-Dimensional State-Space Models
Axel Finke, Sumeetpal S. Singh
We present approximate algorithms for performing smoothing in a class of high-dimensional state-space models via sequential Monte Carlo methods ("particle filters"). In high dimens…