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Regularization theory of the analytic deep prior approach - MaRDI portal

Regularization theory of the analytic deep prior approach (Q5043664)

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scientific article; zbMATH DE number 7596743

Language	Label	Description	Also known as
English	Regularization theory of the analytic deep prior approach	scientific article; zbMATH DE number 7596743

Statements

scholarly article

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Regularization theory of the analytic deep prior approach (English)

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Inverse Problems

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publication date

6 October 2022

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full work available at URL

https://arxiv.org/abs/2205.06493

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zbMATH Keywords

analytic deep prior

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deep image prior

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Tikhonov regularization

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Ivanov regularization

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MaRDI profile type

MaRDI publication profile

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Solving inverse problems using data-driven models

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Computed tomography reconstruction using deep image prior and learned reconstruction methods

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A double regularization approach for inverse problems with noisy data and inexact operator

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Convergence rates of convex variational regularization

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Equivariant neural networks for inverse problems

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A first-order primal-dual algorithm for convex problems with applications to imaging

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Deep neural network structures solving variational inequalities

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Signal Recovery by Proximal Forward-Backward Splitting

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An iterative thresholding algorithm for linear inverse problems with a sparsity constraint

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Regularization by architecture: a deep prior approach for inverse problems

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Convergence rates for Tikhonov regularisation of non-linear ill-posed problems

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A Generative Variational Model for Inverse Problems in Imaging

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A convergence rates result for Tikhonov regularization in Banach spaces with non-smooth operators

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On convergence and convergence rates for Ivanov and Morozov regularization and application to some parameter identification problems in elliptic PDEs

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Joint super-resolution image reconstruction and parameter identification in imaging operator: analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging

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NETT: solving inverse problems with deep neural networks

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Convergence of minimizing sequences

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The Little Engine that Could: Regularization by Denoising (RED)

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Nonlinear total variation based noise removal algorithms

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Well posedness and convergence of some regularisation methods for non-linear ill posed problems

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Overtraining, regularization and searching for a minimum, with application to neural networks

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Relationship of several variational methods for the approximate solution of ill-posed problems

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A Constrained Least Squares Regularization Method for Nonlinear III-Posed Problems

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Regularization and Variable Selection Via the Elastic Net

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Identifiers

Mathematics Subject Classification ID

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zbMATH DE Number

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10.1088/1361-6420/AC9011

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Sitelinks

Mathematics(1 entry)

mardi Publication:5043664

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