Invited Speakers
Jim Berger (Duke)
PBIC and Effective Sample Size 
Carlos Carvalho (Chicago)
On the Long Run Volatility of Stocks
David Dunson (Duke)
High-dimensional nonparametric Bayes variable selection via nonlinear embeddings
Jon Forster (Southampton)
Specification of prior distributions under model uncertainty.
Alan Gelfand (Duke)
Spatial Modeling of presence-only data over large regions
Ed George (Pennsylvania)
Fully Bayes Model Selection with a Generalized g-Prior
Chris Holmes (Oxford)
Bayesian nonparametric clustering of sparse signals
Robert Kohn (UNSW)
Adaptive independent Metropolis-Hastings sampling in challenging models
Athanasios Kottas (UC Santa Cruz)
Nonparametric mixture modeling for Poisson processes
Antonio Lijoi (Pavia)
Gibbs type priors for Bayesian nonparametric inference on species variety
David Madigan (Columbia)
Dynamic Logistic Regression and Dynamic Model Averaging for Binary Classification
Peter Mueller (Texas)
Modeling dependent gene expression
Christian Robert (Paris)
On approximating Bayes factors
David Spiegelhalter (Cambridge)
Model Uncertainty: more than a statistical issue?
Matthew Stephens (Chicago)
Bayesian testing of multivariate outcomes for association with genetic variants
Yee Whye Teh (UCL)
Nanny Wermuth (Gotenburgh)
How can we deal with insecurity regarding choice of models?
Henry Wynn (LSE)
Bayesian information based learning and majorization.
