Bayesian Approach to Inverse Problems.pdf

Bayesian Approach to Inverse Problems PDF

Jérôme Idier

The goal of this book is to deal with inverse problems and regularized solutions using Bayesian statistical tools, with a particular view to signal and image estimation. Chapters 1-3 cover the theoretical notions that make it possible to cast inverse problems within a mathematical framework. Chapters 4-6 address the fundamental inverse problem of deconvolution in a comprehensive manner. Chapters 7 and 8 deal with advanced statistical questions linked to image estimation. Chapters 9-14 put the main tools introduced in the previous chapters into a practical context in important applicative areas, such as astronomy or medical imaging.

Get this from a library! Bayesian approach to inverse problems. [Jérôme Idier;] -- "The goal of this book is to deal with inverse problems and regularized solutions using Bayesian statistical tools, with a particular view to signal and image estimation."--Jacket.

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Bayesian Approach to Inverse Problems.pdf

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Notes actuelles

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Sofya Voigtuh

A Nonparametric Bayesian Approach to Inverse Problems A Nonparametric Bayesian Approach to Inverse Problems ROBERT L. WOLPERT Duke University, USA [email protected] KATJA ICKSTADT MARTIN B. HANSEN Universitat Dortmund, Germany Aalborg Universitet, Denmark¨ [email protected] [email protected] SUMMARY We propose a new method for making inference about an unknown measure Γ(dλ)upon observing some values of …

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Mattio Müllers

The main object of this paper is to present some general concepts of Bayesian inference and more specifically the estimation of the hyperparameters in inverse  ...

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Noels Schulzen

In this work, we develop a novel robust Bayesian approach to inverse problems with data errors following a skew-tdistribution. A hierarchical Bayesian model is developed in the inverse problem setup. The Bayesian approach contains a natural mechanism for regular-ization in the form of a prior distribution, and a LASSO type prior distribution is

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Jason Leghmann

We will treat u, y and η as random variables and define the “solution” of the inverse problem to be the probability distribution of u given y, denoted u|y. This allows ...

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Jessica Kolhmann

The goal of this book is to deal with inverse problems and regularized solutions using the Bayesian statistical tools, with a particular view to signal and image ...