Frank Werner

Professor

Julius-Maximilians-Universität

Germany

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About

Frank Werner is a Professor at Julius-Maximilians-Universität in Germany. His research focuses on statistical inverse problems, regularization techniques, and super-resolution microscopy. Recent publications include work on nuisance parameters in multiscale scanning, optimal regularized hypothesis testing, and the mathematical foundations of ill-posedness in linear operator equations.

Articles (16)

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2022

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2021

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2021

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2021

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2020

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2020

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2020

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2020

Collaborators (3)

Claudia Geisler

Head of department

Institut für Nanophotonik

GERMANY

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Marco Iglesias

Assistant Professor in Scientific Computation

University of Nottingham

UNITED KINGDOM

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Katharina Proksch

Assistant Professor

University of Twente

NETHERLANDS

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Frank Werner

Research Interests

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Articles (16)

Multiscale scanning with nuisance parameters

A Unified Concept of the Degree of Ill-posedness for Compact and Non-Compact Linear Operator Equations in Hilbert Spaces Under the Auspices of the Spectral Theorem

Toward quantitative super-resolution microscopy: molecular maps with statistical guarantees

Adaptive minimax optimality in statistical inverse problems via SOLIT—Sharp Optimal Lepskiĭ-Inspired Tuning

Optimal regularized hypothesis testing in statistical inverse problems

On uniqueness and ill-posedness for the deautoconvolution problem in the multi-dimensional case

Minimax detection of localized signals in statistical inverse problems

On a Dynamic Variant of the Iteratively Regularized Gauss–Newton Method with Sequential Data

Error estimates for variational regularization of inverse problems with general noise models for data and operator

What is resolution? A statistical minimax testing perspective on superresolution microscopy

isoSTED microscopy with water-immersion lenses and background reduction

On the Asymptotical Regularization for Linear Inverse Problems in Presence of White Noise

Variational Multiscale Nonparametric Regression: Algorithms and Implementation

Bump detection in the presence of dependency: Does it ease or does it load?

Multidimensional multiscale scanning in exponential families: Limit theory and statistical consequences

Empirical risk minimization as parameter choice rule for general linear regularization methods

Collaborators (3)

Claudia Geisler

Marco Iglesias

Katharina Proksch

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