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06/09/2022
Unsupervised Learning of the Total Variation Flow
The total variation (TV) flow generates a scale-space representation of ...
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08/08/2021
Image reconstruction in light-sheet microscopy: spatially varying deconvolution and mixed noise
We study the problem of deconvolution for light-sheet microscopy, where ...
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05/05/2021
Two-layer neural networks with values in a Banach space
We study two-layer neural networks whose domain and range are Banach spa...
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03/09/2021
Data driven reconstruction using frames and Riesz bases
We study the problem of regularization of inverse problems adopting a pu...
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06/17/2020
Deeply Learned Spectral Total Variation Decomposition
Non-linear spectral decompositions of images based on one-homogeneous fu...
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05/28/2020
Variational regularisation for inverse problems with imperfect forward operators and general noise models
We study variational regularisation methods for inverse problems with im...
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12/05/2019
Total Variation Regularisation with Spatially Variable Lipschitz Constraints
We introduce a first order Total Variation type regulariser that decompo...
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09/25/2019
Data driven regularization by projection
We demonstrate that regularisation by projection and variational regular...
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03/12/2019
A total variation based regularizer promoting piecewise-Lipschitz reconstructions
We introduce a new regularizer in the total variation family that promot...
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06/26/2018
Convergence rates and structure of solutions of inverse problems with imperfect forward models
The goal of this paper is to further develop an approach to inverse prob...
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08/03/2017
Image reconstruction with imperfect forward models and applications in deblurring
We present and analyse an approach to image reconstruction problems with...
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09/07/2015
