research
∙
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...
share
research
∙
02/20/2023
Bilevel learning of regularization models and their discretization for image deblurring and super-resolution
Bilevel learning is a powerful optimization technique that has extensive...
research
∙
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...
research
∙
03/29/2021
4D Dual-Tree Complex Wavelets for Time-Dependent Data
The dual-tree complex wavelet transform (DT-â„‚WT) is extended to the 4D s...
research
∙
02/18/2021
Convex regularization in statistical inverse learning problems
We consider a statistical inverse learning problem, where the task is to...
research
∙
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...
research
∙
02/27/2020
