a ﬁrst Bayes 250

Took place in Edinburgh, Sept. 5–7, 2011:

Sparse Nonparametric Bayesian Learning from

Big Data David Dunson, Duke University

Classiﬁcation Models and Predictions for Ordered

Data Chris Holmes, Oxford University

Bayesian Variable Selection in Markov Mixture

Models Luigi Spezia, Biomathematics

& Statistics Scotland, Aberdeen

Bayesian inference for partially observed Markov

processes, with application to systems biology

Darren Wilkinson, University of Newcastle

Coherent Inference on Distributed Bayesian

Expert Systems Jim Smith, University of Warwick

Probabilistic Programming John Winn, Microsoft

Research

How To Gamble If You Must (courtesy of the

Reverend Bayes) David Spiegelhalter, University

of Cambridge

Inference and computing with decomposable

graphs Peter Green, University of Bristol

Nonparametric Bayesian Models for Sparse

Matrices and Covariances Zoubin Gharamani,

University of Cambridge

Latent Force Models Neil Lawrence, University of

Sheﬃeld

Does Bayes Theorem Work? Michael Goldstein,

Durham University

Bayesian Priors in the Brain Peggy Series,

University of Edinburgh

Approximate Bayesian Computation for model

selection Christian Robert, Universit´

e

Paris-Dauphine

ABC-EP: Expectation Propagation for

Likelihood-free Bayesian Computation Nicholas

Chopin, CREST–ENSAE

Bayes at Edinburgh University - a talk and tour

Dr Andrew Fraser, Honorary Fellow, University of

Edinburgh

Intractable likelihoods and exact approximate

MCMC algorithms Christophe Andrieu,

University of Bristol

Bayesian computational methods for intractable

continuous-time non-Gaussian time series Simon

Godsill, University of Cambridge

Eﬃcient MCMC for Continuous Time Discrete

State Systems Yee Whye Teh, Gatsby

Computational Neuroscience Unit, University

College London

Adaptive Control and Bayesian Inference Carl

Rasmussen, University of Cambridge

Bernstein - von Mises theorem for irregular

statistical models Natalia Bochkina, University of

Edinburgh