The workshop bringing together, on the one hand, statisticians, computer scientists, and mathematicians and on the other hand applied researchers (especially focusing on epidemiology and public health) with a focus on three interrelated questions:

What is the current practice? How do applied researchers use Bayesian methods, what are the inferential questions they ask and what are the types of scientific and statistical conclusions they want to draw?

What is the methodological state-of-the-art? Which computational methods, e.g. for MCMC or approximate Bayesian inference, do the statisticians (and mathematicians and computer scientists) recommend in practice and why? Should theory guide the answer to these questions? Methodological insights? Under what framework? Is there a role for frequentist analysis of Bayesian methods? Proper scoring rules?

What challenges are there for the future? What problems can applied researchers not currently solve, and are they fundamentally statistical, computational, or philosophical? What problems are methodological and theory researchers working on, for which real, applied problems and datasets could be useful to motivate further development?

Find out more and register

For up-to-date information about this workshop, and to register, please see the Scalable Bayesian Inference in Applied fields website.