1. Integrated Objective Bayesian Estimation and Hypothesis Testing, J. M. Bernardo
2. Dynamic Stock Selection Strategies: A Structured Factor Model Framework, C. M. Carvalho, H. F. Lopes, O. Aguilar
3. Free Energy Sequential Monte Carlo, Application to Mixture Modelling, Chopin, N. and Jacob, P.
4. Moment Priors for Bayesian Model Choice with Applications to Directed Acyclic Graphs, Consonni G. and La Rocca, L.
5. Nonparametric Bayes Regression and Classification Through Mixtures of Product Kernels, Dunson, D. B. and Bhattacharya, A.
6. Bayesian Variable Selection for Random Intercept Modeling of Gaussian and non-Gaussian Data., Fruhwirth-Schnatter, S. and Wagner, H.
7. External Bayesian Analysis for Computer Simulators, Goldstein, M.
8. Optimization Under Unknown Constraints, Gramacy, R. B. and Lee, H. K. H.
9. Using TPA for Bayesian Inference, Huber, M. and Schott, S.
10. Nonparametric Bayesian Networks, Ickstadt, K., Bornkamp, B., Grzegorczyk, M., Wiecorek, J., Sherriff, M. R., Grecco, H. E. and Zamir, E.
11. Particle Learning for Sequential Bayesian Computation, Lopes, H. F., Carvalho, C. M., Johannes, M. S. and Polson, N. G.
12. Rotating Stars and Revolving Planets: Bayesian Exploration of the Pulsating Sky, Loredo, T. J.
13. Association Tests that Accommodate Genotyping Uncertainty, Louis, T. A., Carvalho, B. S., Fallin, M. D., Irizarryi, R. A., Li, Q. and Ruczinski, I.
14. Bayesian Methods in Pharmacovigilance, Madigan, D., Ryan, P., Simpson, S. and Zorych, I.
15. Approximating Max-Sum-Product Problems using Multiplicative Error Bounds, Meek, C. and Wexler, Y.
16. What's the H in H-likelihood: A Holy Grail or an Achilles' Heel?, Meng, X.-L.
17. Shrink Globally, Act Locally: Sparse Bayesian Regularization and Prediction, Polson, N. G. and Scott, J. G.
18. Bayesian Models for Sparse Regression Analysis of High Dimensional Data, Richardson, S., Bottolo, L. and Rosenthal, J. S.
19. Transparent Parametrizations of Models for Potential Outcomes, Richardson, T. S., Evans, R. J. and Robins, J. M.
20. Modelling Multivariate Counts Varying Continuously in Space, Schmidt, A. M. and Rodriguez, M. A.
21. Characterizing Uncertainty of Future Climate Change Projections using Hierarchical Bayesian Models, Tebaldi, C., Sanso, B. and Smith, R. L.
22. Bayesian Models for Variable Selection that Incorporate Biological Information, Vannucci, M. and Stingo, F. C.
23. Parameter Inference for Stochastic Kinetic Models of Bacterial Gene Regulation: A Bayesian Approach to Systems Biology, Wilkinson, D. J.