
Identifying Untrustworthy Predictions in Neural Networks by Geometric Gradient Analysis
The susceptibility of deep neural networks to untrustworthy predictions,...
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Convex regularization in statistical inverse learning problems
We consider a statistical inverse learning problem, where the task is to...
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Sampled Nonlocal Gradients for Stronger Adversarial Attacks
The vulnerability of deep neural networks to small and even imperceptibl...
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Meanfield optimal control for biological pattern formation
We propose a meanfield optimal control problem for the parameter identi...
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Adaptive Superresolution in Deconvolution of Sparse Peaks
The aim of this paper is to investigate superresolution in deconvolution...
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Sequentially optimized projections in Xray imaging
This work applies Bayesian experimental design to selecting optimal proj...
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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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Total Variation Regularisation with Spatially Variable Lipschitz Constraints
We introduce a first order Total Variation type regulariser that decompo...
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An entropic Landweber method for linear illposed problems
The aim of this paper is to investigate the use of an entropic projectio...
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An entropic projection method for linear illposed problems
The aim of this paper is to investigate the use of an entropic projectio...
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Reconstruction Methods in THz Singlepixel Imaging
The aim of this paper is to discuss some advanced aspects of image recon...
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A total variation based regularizer promoting piecewiseLipschitz reconstructions
We introduce a new regularizer in the total variation family that promot...
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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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Computing Nonlinear Eigenfunctions via Gradient Flow Extinction
In this work we investigate the computation of nonlinear eigenfunctions ...
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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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Adaptive Regularization of Some Inverse Problems in Image Analysis
We present an adaptive regularization scheme for optimizing composite en...
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Nonlinear Spectral Image Fusion
In this paper we demonstrate that the framework of nonlinear spectral de...
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Block Compressive Sensing of Image and Video with Nonlocal Lagrangian Multiplier and Patchbased Sparse Representation
Although block compressive sensing (BCS) makes it tractable to sense lar...
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Adaptive Regularization in Convex Composite Optimization for Variational Imaging Problems
We propose an adaptive regularization scheme in a variational framework ...
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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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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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Nonlinear Spectral Analysis via Onehomogeneous Functionals  Overview and Future Prospects
We present in this paper the motivation and theory of nonlinear spectral...
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First order algorithms in variational image processing
Variational methods in imaging are nowadays developing towards a quite u...
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Martin Burger
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