Baey, Stochastic Algorithms for Nonlinear Mixed Models 2 G. Band, Bayesian Analysis of Genetic Association with Severe Malaria 3 M. Banterle, Sufficient Dimension Reduction for ABC via RKHS. 4 P. Birrell, Efficient Real-‐Time Statistical Modeling for Pandemic Influenza 5 A. Bitto, Time-‐Varying Parameter Models – Achieving Shrinkage and Variable Selection 6 A. Calmo, Bayesian Modeling of Network Heterogeneity. 7 Y. Chen, A Comparison of Sequential Monte Carlo Techniques in a Plant Growth Model 8 P. Conrad, Asymptotically Exact MCMC Algorithms for Computationally Expensive Models via Local Approximations 9 N. Duforet-‐ Frebourg Genome Scans for Local Adaptations: A Bayesian Factor Model. 10 A. Durmus, New Bounds for the Sub-‐Geometric Convergence of Markov Chains in Wasserstein Metric and Application to the Pre-‐Conditionned Crank Nickolson Algorithm. 11 R. Dutta, Sequential Mixture Models on Model Space: Retrieval of Experiments. 12 M. Farag, A Strategy for Calibrating Time Series Epidemic Simulators. 13 A. Finke, Investigation of Exactly Approximated Rao-‐Blackwellised Particle Filters. 14 B. Fosdick, Bayesian Inference for Network Models with Additive and Multiplicative Effects. 15 E. Fox, Gaussian Processes on the Brain: Heteroscedasticity, Nonstationarity and Long-‐Range Dependencies. 16 E. Frichot, Testing for Associations between Loci and Environmental Gradients using Latent Factor Mixed Models. 17 E. Gayawan, Spatial Bayesian Semi-‐Parametric Analyses of Childhood Mortality in Nigeria: Estimate from Mortality Index. 18 G. Goh, Bayesian Model Selection for Circular Data with Wrapped Distribution. 19 R. Gonzales, Modeling Hyperinflation Phenomena: A Bayesian Approach. 20 C. Grazian, Approximate Bayesian Computation for the Elimination of Nuisance Parameters. 21 M. Galloway, Time-‐to-‐default Analysis of Mortgage Portfolios. 22 M. Gutmann, Classifier ABC. 23 M. Gutmann, Bayesian Optimization for Likelihood-‐Free Estimation. 24 Z. van Havre, Overfitting Mixture Models and Hidden Markov Models with an Unknown Number of States. 25 J. Heydari, Bayesian Hierarchical Modeling for Inferring Genetic Interactions. 26 V. Jaaskinen, Sparse Markov Chains for Sequence Data. 27 P. Jacob, Path Storage in the Particle Filter. 28 X. Jiao, Combining the Marginal Data Augmentation and the Ancillarity-‐Sufficiency Interweaving Strategy to Further Improve the Convergence of Data Augmentation Algorithm. 29 G. Kastner, Analysis of Multivariate Financial Time Series via Bayesian Factor Stochastic Volatility Models. 30 M. Katzfuss, Statistical Inference for Massive Distributed Spatial Data Using Low-‐Rank Models. 31 K. Kamatani, Local Consisency of Markov Chain Monte Carlo with some Applications. 32 K. Kamari, A discussion of Bayesian Analysis: On Applying Non-‐Informative Priors.
Sequential Kernel Herding: Frank-‐Wolfe Optimization for Particle Filtering. 2 W. Li, Efficient Sequential Monte Carlo with Multiple Proposal. 3 M. Liechty, Multivariate Sufficient Statistics Using Kronecker Products. 4 S. Livingstone, A Tutorial on Diffusions on Manifolds for MCMC. 5 A. Martins, Constraining the Milky Way Formation and Evolution with MCMC/ABC Method. 6 L. Martino, Adaptive Sticky Metropolis. 7 L. Martino, An Iterated Batch Importance Sampler Driven by an MCMC Algorithm. 8 F. Medina Aguayo, The Pseudo-‐Marginal Approach to MCMC. 9 P. Minvielle, Particle MCMC for Inverse Scattering in Microwave Control. 10 M. Moores, Scalable Bayesian Computation for Intractable Likelihoods in Image Analysis. 11 Z. Naulet, Nonparametric Bayesian Kernel-‐Based Function Estimation. 12 W. Niemiro, Adaptive Monte Carlo Maximum Likelihood Based on Importance Sampling with Resampling. 13 H. Nyman, Stratified Gaussian Graphical Models. 14 J. Owen, Scalable Inference for Intractable Markov Processes Using ABC and PMCMC. 15 A. Pakman, Auxilliary-‐Variable Exact Hamiltonian Monte Carlo Samplers for Binary Distributions. 16 M. Parno, Using Multiscale Structure and Transport Maps in MCMC for High-‐Dimensional Inverse Problems. 17 J. Pensar, Bayesian Learning of Labeled Directed Acyclic Graphs Using Non-‐Reversible MCMC. 18 J. Pitchforth, Combining Complex Systems Models for Better International Passenger Processing Operations. 19 M. Pollock, Jump Diffusion Barriers. 20 A. Posekany, Merging Parallel MCMC Output for Horizontally Partitioned Data. 21 V. Rockova, Sequential EMVS Mode Detection for Posterior Reconstruction. 22 D. Rudolf, On the Hybrid Slice Sampler. 23 S. Robinson, Structural Functional Time Series Models. 24 A. Sabourin, Bayesian Dirichlet Mixture Model for Multivariate Extremes: A Reparameterization 25 A. Schreck, A Shrinkage-‐Thresholding Metropolis Adjusted Langevin Algorithm for Bayesian Variable Selection. 26 R. Steorts, Will the Real Steve Fienberg Please Stand up: Getting to Know a Population from Multiple Incomplete files. 27 J. Stoehr, ABC Model Choice between Hidden Gibbs Random Fields Based on Geometric Summary Statistics. 28 D. Tang, Hamiltonian Monte Carlo with Local Stochastic Step-‐Size. 29 A. Todeschini BiiPS: A Software for Inference in Bayesian Graphical Models with Sequential Monte Carlo Methods. 30 V. Torman, Bayesian Analysis of the Log-‐Binomial Model: A Comparison with the Frequentist Approach for the Estimation of the Relative Risk. 31 S. Tsepletidou, Computational Bayesian Tools for Modeling the Aging Process in Escherichia Coli. 32 E. Vernet, Posterior Consistency for Nonparametric Hidden Markov Models with Finite State Space. 33 H. Wang Scaling it Up: Stochastic Search Structure Learning in Graphical Models. 34 K. Wolny, Robust Metropolis-‐Adjusted Langevin Algorithms. 35 G. Zanella, Bayesian Complementary Clustering, MCMC for Data Association and Anglo-‐Saxon Placenames. 36 W. Zhu, Bootstrap Likelihood and Bayesian Computations.