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03/01/2023
Trust your source: quantifying source condition elements for variational regularisation methods
Source conditions are a key tool in variational regularisation to derive...
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12/23/2022
On a fixed-point continuation method for a convex optimization problem
We consider a variation of the classical proximal-gradient algorithm for...
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12/23/2021
Shearlet-based regularization in statistical inverse learning with an application to X-ray tomography
Statistical inverse learning theory, a field that lies at the intersecti...
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06/11/2021
Learning the optimal regularizer for inverse problems
In this work, we consider the linear inverse problem y=Ax+ϵ, where A X→ ...
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02/18/2021
Convex regularization in statistical inverse learning problems
We consider a statistical inverse learning problem, where the task is to...
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06/02/2020
Deep neural networks for inverse problems with pseudodifferential operators: an application to limited-angle tomography
We propose a novel convolutional neural network (CNN), called ΨDONet, de...
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06/16/2019
