Frank Werner
Frank Werner
Professor for Inverse Problems, Julius-Maximilians-Universität Würzburg
Verified email at - Homepage
Cited by
Cited by
Inverse Problems with Poisson data: statistical regularization theory, applications and algorithms
T Hohage, F Werner
Inverse Problems 32 (9), 093001 (56pp), 2016
Iteratively regularized Newton-type methods for general data misfit functionals and applications to Poisson data
T Hohage, F Werner
Numerische Mathematik 123 (4), 745-779, 2013
Convergence rates in expectation for Tikhonov-type regularization of inverse problems with Poisson data
F Werner, T Hohage
Inverse Problems 28 (10), 104004, 2012
Convergence Rates for Exponentially Ill-Posed Inverse Problems with Impulsive Noise
C König, F Werner, T Hohage
SIAM Journal on Numerical Analysis 54 (1), 341-360, 2016
Multiscale scanning in inverse problems
K Proksch, F Werner, A Munk
The Annals of Statistics 46 (6B), 3569-3602, 2018
Convergence Rates for Inverse Problems with Impulsive Noise
T Hohage, F Werner
SIAM Journal on Numerical Analysis 52 (3), 1203-1221, 2014
Inverse problems with Poisson data: Tikhonov-type regularization and iteratively regularized Newton methods
F Werner
Der Andere Verlag, 2012
Multidimensional multiscale scanning in Exponential Families: Limit theory and statistical consequences
C König, A Munk, F Werner
The Annals of Statistics 48 (2), 655-678, 2020
On convergence rates for iteratively regularized Newton-type methods under a Lipschitz-type nonlinearity condition
F Werner
Journal of Inverse and Ill-Posed Problems 23 (1), 75-84, 2015
Bump detection in heterogeneous Gaussian regression
F Enikeeva, A Munk, F Werner
Bernoulli 24 (2), 1266-1306, 2018
Convergence Analysis of (Statistical) Inverse Problems under Conditional Stability Estimates
F Werner, B Hofmann
Inverse Problems 36 (1), 015004, 2020
Empirical Risk Minimization as Parameter Choice Rule for General Linear Regularization Methods
H Li, F Werner
Annales de l’Institut Henri Poincaré 56 (1), 405-427, 2020
Adaptivity and Oracle Inequalities in Linear Statistical Inverse Problems: A (Numerical) Survey
F Werner
New Trends in Parameter Identification for Mathematical Models, 291-316, 2018
Statistical foundations of nanoscale photonic imaging
A Munk, T Staudt, F Werner
Nanoscale Photonic Imaging, 125-143, 2020
Bump detection in the presence of dependency: Does it ease or does it load?
F Enikeeva, A Munk, M Pohlmann, F Werner
Bernoulli 26 (4), 3280-3310, 2020
Photonic imaging with statistical guarantees: From multiscale testing to multiscale estimation
A Munk, K Proksch, H Li, F Werner
Nanoscale Photonic Imaging, 283-312, 2020
Discussion of "Hypothesis testing by convex optimization" by A. Goldenshluger, A. Juditsky and A. Nemirovski.
A Munk, F Werner
Electronic Journal of Statistics 9 (2), 1720-1722, 2015
On the asymptotical regularization for linear inverse problems in presence of white noise
S Lu, P Niu, F Werner
SIAM/ASA Journal on Uncertainty Quantification 9 (1), 1–28, 2021
What is resolution? A statistical minimax testing perspective on super-resolution microscopy
G Kulaitis, A Munk, F Werner
Accepted for The Annals of Statistics, 2020
Variational multiscale nonparametric regression: Algorithms
M del Alamo, H Li, A Munk, F Werner
Algorithms 13 (11), 296, 2020
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