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Published in 2019 at "Statistical Inference for Stochastic Processes"
DOI: 10.1007/s11203-021-09239-3
Abstract: In this paper we address the problem of estimating the posterior distribution of the static parameters of a continuous-time state space model with discrete-time observations by an algorithm that combines the Kalman filter and a…
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Keywords:
filter;
estimation;
posterior distribution;
particle filter ... See more keywords
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Published in 2017 at "Computer Methods in Applied Mechanics and Engineering"
DOI: 10.1016/j.cma.2017.08.016
Abstract: In this work we propose and analyze a Hessian-based adaptive sparse quadrature to compute infinite-dimensional integrals with respect to the posterior distribution in the context of Bayesian inverse problems with Gaussian prior. Due to the…
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Keywords:
posterior distribution;
adaptive sparse;
sparse quadrature;
quadrature ... See more keywords
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Published in 2022 at "IEEE Signal Processing Letters"
DOI: 10.1109/lsp.2022.3169439
Abstract: This letter deals with Gaussian approximation of complicated posterior distribution involved in the Bayesian paradigm for nonlinear dynamic systems. A general formulation for Gaussian approximation is first provided by equivalently representing posterior distribution as a…
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Keywords:
penalized kullback;
minimization;
posterior distribution;
approximation ... See more keywords
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Published in 2018 at "Australasian Journal of Dermatology"
DOI: 10.1111/ajd.12683
Abstract: ment effect, and (ii) no meaningful treatment effect. This was achieved by integrating the priors and the likelihoods over reasonable upper and lower bounds. In contrast, as the author points out, it is possible to…
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Keywords:
posterior distribution;
clinic application;
effect;
application ingenol ... See more keywords
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Published in 2021 at "European Journal of Neurology"
DOI: 10.1111/ene.14993
Abstract: Cerebral amyloid angiopathy (CAA) is a well‐recognized contributor to cognitive decline in the elderly. The posterior cortical predilection of CAA pathology would cause visuospatial dysfunction, which is still underexplored. We aimed to investigate whether the…
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Keywords:
amyloid angiopathy;
cerebral amyloid;
posterior distribution;
dysfunction ... See more keywords
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Published in 2023 at "Statistical Science"
DOI: 10.1214/22-sts868
Abstract: Gaussian process (GP) regression is computationally expensive in spatial applications involving massive data. Various methods address this limitation, including a small number of Bayesian methods based on distributed computations (or the divide-and-conquer strategy). Focusing on…
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Keywords:
distributed bayesian;
inference massive;
posterior distribution;
massive spatial ... See more keywords