Browsing by Subject "Gaussian processes"
Now showing items 1-7 of 7
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(2022-04-20)In many applications, spatial data often display heterogeneous dependence patterns and may be subject to irregular geographic constraints. In light of these challenges, this dissertation develops several novel Bayesian ...
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(2019-05-28)This dissertation contains two independent projects: the first project develops a general methodology for solving the Positive–Unlabeled (PU) learning problem, and the second project creates a hierarchical Bayesian model ...
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(2014-07-08)Big Data refers to the complexity, high-dimensionality, and high volume of information which are common features in many contemporary engineering applications. In the context of Big Data, however, specific treatments are ...
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(Texas A&M University. Libraries, 1981)Parzen (1979) suggests a location and scale model for the quantile function (inverse distribution function) of a random variable. We extend this model to the two sample and k-sample problems and some results are given ...
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(2018-05-04)Laser Powder-Bed Fusion processes capable of processing metallic materials are a set of relatively new and emerging Additive Manufacturing technologies that offer attractive potential and capabilities (e.g., design freedom, ...
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(2020-06-18)We propose a family of filtering methods for deriving the filtering distribution in the context of a high-dimensional state-space model. In the first chapter, we develop and describe in detail the basic method, which can ...
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(2020-07-21)Bayesian methodology has been widely explored and applied to broad fields due to its natural ability of uncertainty quantification, also the flexibility to model specific statistical problems and incorporate non-regular ...