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04/02/2023
Resolution-Invariant Image Classification based on Fourier Neural Operators
In this paper we investigate the use of Fourier Neural Operators (FNOs) ...
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12/14/2022
Convergent Data-driven Regularizations for CT Reconstruction
The reconstruction of images from their corresponding noisy Radon transf...
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09/15/2022
Spectral Total-Variation Processing of Shapes – Theory and Applications
In this work we present a comprehensive analysis of total variation (TV)...
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07/01/2022
Analysis of Kinetic Models for Label Switching and Stochastic Gradient Descent
In this paper we provide a novel approach to the analysis of kinetic mod...
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12/08/2021
Variational Regularization in Inverse Problems and Machine Learning
This paper discusses basic results and recent developments on variationa...
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10/24/2021
Learning convex regularizers satisfying the variational source condition for inverse problems
Variational regularization has remained one of the most successful appro...
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07/13/2021
A Diffuse Interface Model for Cell Blebbing Including Membrane-Cortex Coupling with Linker Dynamics
The aim of this paper is to develop suitable models for the phenomenon o...
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06/04/2021
Neural Architecture Search via Bregman Iterations
We propose a novel strategy for Neural Architecture Search (NAS) based o...
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05/18/2021
Gradient Flows, Nonlinear Power Methods, and Computation of Nonlinear Eigenfunctions
This chapter describes how gradient flows and nonlinear power methods in...
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05/10/2021
A Bregman Learning Framework for Sparse Neural Networks
We propose a learning framework based on stochastic Bregman iterations t...
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02/24/2021
Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis
The susceptibility of deep neural networks to untrustworthy predictions,...
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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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11/05/2020
Sampled Nonlocal Gradients for Stronger Adversarial Attacks
The vulnerability of deep neural networks to small and even imperceptibl...
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09/21/2020
Mean-field optimal control for biological pattern formation
We propose a mean-field optimal control problem for the parameter identi...
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07/10/2020
Adaptive Superresolution in Deconvolution of Sparse Peaks
The aim of this paper is to investigate superresolution in deconvolution...
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06/22/2020
Sequentially optimized projections in X-ray imaging
This work applies Bayesian experimental design to selecting optimal proj...
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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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06/24/2019
An entropic Landweber method for linear ill-posed problems
The aim of this paper is to investigate the use of an entropic projectio...
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06/24/2019
An entropic projection method for linear ill-posed problems
The aim of this paper is to investigate the use of an entropic projectio...
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03/21/2019
Reconstruction Methods in THz Single-pixel Imaging
The aim of this paper is to discuss some advanced aspects of image recon...
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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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03/07/2019
Variational Graph Methods for Efficient Point Cloud Sparsification
In recent years new application areas have emerged in which one aims to ...
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02/27/2019
Computing Nonlinear Eigenfunctions via Gradient Flow Extinction
In this work we investigate the computation of nonlinear eigenfunctions ...
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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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05/09/2017
Adaptive Regularization of Some Inverse Problems in Image Analysis
We present an adaptive regularization scheme for optimizing composite en...
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03/23/2017
Nonlinear Spectral Image Fusion
In this paper we demonstrate that the framework of nonlinear spectral de...
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03/15/2017
Block Compressive Sensing of Image and Video with Nonlocal Lagrangian Multiplier and Patch-based Sparse Representation
Although block compressive sensing (BCS) makes it tractable to sense lar...
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09/08/2016
Adaptive Regularization in Convex Composite Optimization for Variational Imaging Problems
We propose an adaptive regularization scheme in a variational framework ...
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07/12/2016
A Variational Model for Joint Motion Estimation and Image Reconstruction
The aim of this paper is to derive and analyze a variational model for t...
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12/01/2015
On Optical Flow Models for Variational Motion Estimation
The aim of this paper is to discuss and evaluate total variation based r...
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10/05/2015
Nonlinear Spectral Analysis via One-homogeneous Functionals - Overview and Future Prospects
We present in this paper the motivation and theory of nonlinear spectral...
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12/13/2014
