Saifuddin Syed, Vittorio Romaniello, Trevor Campbell, and Alexandre Bouchard-Côté, whom I met and discussed with on my “last” trip to UBC, on December 2019, just arXived a paper on parallel tempering (PT), making the choice of tempering path an optimisation problem. They address the touchy issue of designing a sequence of tempered targets when the […]

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## parallel tempering on optimised paths

May 20, 2021## parallel MCMC

September 9, 2020Yesterday, I remotely took part in the thesis defence of Balazs Nemeth, at Hasselt University, Belgium. As the pandemic conditions were alas still too uncertain to allow for travelling between France and Belgium… The thesis is about parallel strategies for speeding up MCMC, although the title is “Message passing computational methods with pharmacometrics applications”, as […]

## parallelising MCMC via random forests

November 26, 2019We have just arXived a new paper written with my former PhD student Wu Changye on the use of random forest regressions to learn the partial posteriors simulated in divide-and-conquer MCMC, when the whole data set into batches, runs MCMC algorithms separately over each batch to produce samples of parameters. Here, we use each resulting […]

## parallelizable sampling method for parameter inference of large biochemical reaction models

June 18, 2018I came across this older (2016) arXiv paper by Jan Mikelson and Mustafa Khammash [antidated as of April 25, 2018] as another version of nested sampling. The novelty of the approach is in applying nested sampling for approximating the likelihood function in the case of involved hidden Markov models (although the name itself does not […]