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Bishop, C. M. and Lasserre, J.: Generative or Discriminative? Getting the Best of Both Worlds; Brooks, S. P., Manolopoulou, I. and Emerson, B. C.: Assessing the Effect of Genetic Mutation - A Bayesian Framework for Determining Population History from DNA Sequence Data; Ghosh, J. K. and Chakrabarti, A.: Some Aspects of Bayesian Model Selection for Prediction; Clyde, M. A. and Wolpert, R. L.: Nonparametric Function Estimation Using Overcomplete Dictionaries; Del Moral, P., Doucet, A. and Jasra, A.: Sequential Monte Carlo for Bayesian Computation; Gamerman, D., Salazar, E. and Reis, E. A.: Dynamic Gaussian Process Priors, with Applications to The Analysis of Space-time Data; Gelfand, A. E., Guindani, M. and Petrone, S.: Bayesian Nonparametric Modelling for Spatial Data Using Dirichlet Processes; Ghahramani, Z., Griffiths, T. L. and Sollich, P.: Bayesian Nonparametric Latent Feature Models; GirÁon, F. J., Moreno, E. and Casella, G.: Objective Bayesian Analysis of Multiple Changepoints for Linear Models; Holmes, C. C. and Pintore, A.: Bayesian Relaxation: Boosting, The Lasso, and other L norms; Little, R. J. A. and Zheng, H.: The Bayesian Approach to the Analysis of Finite Population Surveys; Merl, D. and Prado, R.: Detecting selection in DNA sequences: Bayesian Modelling and Inference; Mira, A. and Baddeley, A.: Deriving Bayesian and frequentist estimators from time-invariance estimating equations: a unifying approach; M®uller, P., Parmigiani, G. and Rice, K.: FDR and Bayesian Multiple Comparisons Rules; Raftery, A., Newton, M., Satagopan, J. and Krivitsky, P.: Estimating the Integrated Likelihood via Posterior Simulation Using the Harmonic Mean Identity.; Rousseau, J.: Approximating Interval Hypothesis: p-values and Bayes Factors; Schack, R.: Bayesian Probability in Quantum Mechanics; Schmidler, S. C.: Fast Bayesian Shape Matching Using Geometric Algorithms; Skilling, J.: Nested Sampling for Bayesian Computations; Sun, D. and Berger, J. O.: Objective Bayesian Analysis for the Multivariate Normal Model; CONTRIBUTED PAPERS; Almeida, C. and Mouchart, M.: Bayesian Encompassing Specification Test Under Not Completely Known Partial Observability; Bernardo, J. M. and PÁerez, S.: Comparing Normal Means: New Methods for an Old Problem; Cano, J. A., Kessler, M. and SalmerÁon, D.: Integral Priors for the One Way Random Effects Model; Carvalho, C. M. and West, M.: Dynamic Matrix-Variate Graphical Models; Cowell, R. G., Lauritzen, S.L. and Mortera, J.: A Gamma Model for DNA Mixture Analyses; Denham, R. J. and Mengersen, K.: Geographically Assisted Elicitation of Expert Opinion for Regression Models; DukiÁc, V. and Dignam, J.: Hierarchical Multiresolution Hazard Model for Breast Cancer Recurrence; Hutter, M.: Bayesian Regression of Piecewise Constant Functions; Jirsa, J., Quinn, A. and Varga, F.: Identification of Thyroid Gland Activity in Radiotherapy.; Kokolakis, G. and Kouvaras, G.: Partial Convexification of Random Probability Measures; Ma, H. and Carlin, B. P.: Bayesian Multivariate Areal Wombling; Madrigal, A. M.: Cluster Allocation Design Networks; Mertens, B. J. A.: Logistic Regression Modelling of Proteomic Mass Spectra in a Case-Control Study on Diagnosis for Colon Cancer; M‗ller, J. and Mengersen, K.: Ergodic Averages Via Dominating Processes; Perugia, M.: Bayesian Model Diagnostics Based on Artificial Autoregressive Errors; Short, M. B., Higdon, D. M. and Kronberg, P. P.: Estimation of Faraday Rotation Measures of the Near Galactic Sky, Using Gaussian Process Models; Spitzner, D. J.: An Asymptotic Viewpoint on High-Dimensional Bayesian Testing; Wallstrom, T. C.: The Marginalization Paradox and Probability Limits Xing, E. P. and Sohn, K.-A.: A Hidden Markov Dirichlet Process Model for Genetic Recombination in Open Ancestral Space

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