Birs- 14w5125: Advances in Scalable Bayesian Computation

  1. Title:
    Probabilistic computing for Bayesian inference

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  2. Title:
    On non-negative unbiased estimators

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  3. Title:
    Marginal Sampler for σ-Stable Poisson-Kingman Mixture Models

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  4. Title:
    A new approach to probabilistic programming inference

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  5. Title:
    LATKES in Space: Fitting spatial Markov chain models

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  6. Title:
    Statistical Regular Pavings for Bayesian Non-parametric Density Estimation

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  7. Title:
    A scalable Bayesian changepoint methodology for large space-time data sets

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  8. Title:
    Reparameterisations for Particle MCMC

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  9. Title:
    2-for-1: Stochastic Gradient Hamiltonian Monte Carlo and Bayesian Learning of DPP Kernels

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  10. Title:
    Model-Based Image Segmentation / Efficiency of MCMC in Parametric Models

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  11. Title:
    Learning Structured, Robust, and Multimodal Models

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  12. Title:
    Bayes and Big Data: The Consensus Monte Carlo Algorithm

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  13. Title:
    On the role of interaction in sequential Monte Carlo algorithm

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  14. Title:
    Parallelisation strategies for Monte Carlo algorithms

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  15. Title:
    Sequential Quasi-Monte Carlo

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  16. Title:
    Merging parallel MCMC output for horizontally partitioned data

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  17. Title:
    Hierarchical Bayesian Methods in Modern Industrial Statistics

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  18. Title:
    Scaling Bayesian models for large-scale infectious disease surveillance

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