3 citations · 4 across the 4 of their papers we have counts for
3 papers · 1 filter
A subsampling approach for Bayesian model selection
Jon Lachmann, Geir Storvik, Florian Frommlet +1
It is common practice to use Laplace approximations to compute marginal likelihoods in Bayesian versions of generalised linear models (GLM). Marginal likelihoods combined with mode…
Reversible Genetically Modified Mode Jumping MCMC
Aliaksandr Hubin, Florian Frommlet, Geir Storvik
In this paper, we introduce a reversible version of a genetically modified mode jumping Markov chain Monte Carlo algorithm (GMJMCMC) for inference on posterior model probabilities…
Deep Bayesian regression models
Aliaksandr Hubin, Geir Storvik, Florian Frommlet
Regression models are used for inference and prediction in a wide range of applications providing a powerful scientific tool for researchers and analysts from different fields. In…