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Showing 1 to 5 of 5 for “"nonparametric Bayes"”.

  1. Bayesian Nonparametric Modeling and Theory for Complex Data

    … and methodological problems associated with Bayesian modeling of infinite dimensional `objects', popularly called nonparametric Bayes. The term `infinite dimensional object' can refer to a density, a conditional density, a regression surface or even a manifold. Although Bayesian density …

    duke Repository record for Bayesian Nonparametric Modeling and Theory for Complex Data (opens in a new tab)

  2. Scalable sparsity structure learning using Bayesian methods

    … and theory. In this thesis we develop scalable Bayesian algorithms based on EM algorithm and variational inference to learn sparsity structure in various models. Estimation consistency and selection consistency of our methods are established. First, a nonparametric Bayes estimator is proposed …

    uiuc Repository record for Scalable sparsity structure learning using Bayesian methods (opens in a new tab)

  3. Bayesian modelling and sampling strategies for ordering and clustering problems with a focus on next-generation sequencing data

    … of longitudinal information. I developed a new, Bayesian, way of reconstructing this information computationally, sampling orders efficiently using MCMC on a space of permutations. This Bayesian approach provides novel insights into biological phenomena and experimental artefacts. The second part …

    cambridge Repository record for Bayesian modelling and sampling strategies for ordering and clustering problems with a focus on next-generation sequencing data (opens in a new tab)

  4. Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-08-01

    uiuc Repository record for Dimension reduction methods for quantifying local variable importance and the statistical analysis of network data (opens in a new tab)

  5. Consistency of nonparametric Bayesian methods for two statistical inverse problems arising from partial differential equations

    … such statistical inverse problems is through Bayesian methodology. This thesis investigates the theoretical performance of the Bayesian approach in two particular cases. The first model considered is the advection-diffusion equation. Kolmogorov’s equations link this partial differential …

    cambridge Repository record for Consistency of nonparametric Bayesian methods for two statistical inverse problems arising from partial differential equations (opens in a new tab)