Munk, Axel

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21.09.2022

Distribution of Distances based Object Matching: Asymptotic Inference

Authors Weitkamp CA, Proksch K, Tameling C, Munk A Journal Journal of the American Statistical Association Citation J Am Stat Assoc. 1-32. 2022. Abstract In this paper, we aim to provide a statistical theory for object matching based on a lower bound of the Gromov-Wasserstein distance related to the distribution
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16.06.2022

The Statistics of Circular Optimal Transport

Authors Hundrieser S, Klatt M, Munk A Journal Directional Statistics for Innovative Applications Citation SenGupta, A., Arnold, B.C. (eds) Directional Statistics for Innovative Applications. Forum for Interdisciplinary Mathematics. Springer, Singapore. Abstract Empirical optimal transport (OT) plans and distances provide effective tools to compare and statistically match probability measures defined on
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01.06.2022

Statistical Methods for Minimax Estimation in Linear Models with Unknown Design Over Finite Alphabets

Authors Behr M, Munk A Journal SIAM Journal on Mathematics of Data Science Citation SIAM Journal on Mathematics of Data Science 4(2):490-513. Abstract We provide a minimax optimal estimation procedure for F and W in matrix valued linear models Y = F W + Z where the parameter matrix W
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01.03.2022

A Variational View on Statistical Multiscale Estimation

Authors Haltmeier M, Li H, Munk A Journal Annual Review of Statistics and Its Application Citation Annu. Rev. Stat. Appl. 2022.9:343-372. Abstract We present a unifying view on various statistical estimation techniques including penalization, variational, and thresholding methods. These estimators are analyzed in the context of statistical linear inverse problems
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28.02.2022

Randomised Wasserstein Barycenter Computation: Resampling with Statistical Guarantees

Authors Heinemann F, Munk A, Zemel Y Journal SIAM Journal on Mathematics of Data Science Citation SIAM Journal on Mathematics of Data Science 2022 4:1, 229-259. Abstract We propose a hybrid resampling method to approximate finitely supported Wasserstein barycenters on large-scale datasets, which can be combined with any exact solver.
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01.12.2021

Posterior analysis of n in the binomial (n,p) problem with both parameters unknown — with applications to quantitative nanoscopy

Authors Schmidt-Hieber J, Schneider LF, Staudt T, Krajina A, Aspelmeier T, Munk A Journal The Annals of Statistics Citation Ann. Statist. 49(6): 3534-3558 (December 2021). Abstract Estimation of the population size n from k i.i.d. binomial observations with unknown success probability p is relevant to a multitude of applications and
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01.08.2021

What is resolution? A statistical minimax testing perspective on super-resolution microscopy

Authors Kulaitis G, Munk A, Werner F Journal The Annals of Statistic Citation Ann. Statist. 49(4): 2292-2312 (August 2021). Abstract As a general rule of thumb the resolution of a light microscope (i.e., the ability to discern objects) is predominantly described by the full width at half maximum (FWHM) of
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01.06.2021

Frame-constrained Total Variation Regularization for White Noise Regression

Authors del Álamo M, Li H, Munk A Journal The Annals of Statistics Citation Ann. Statist. 49(3): 1318-1346 (June 2021). Abstract Despite the popularity and practical success of total variation (TV) regularization for function estimation, surprisingly little is known about its theoretical performance in a statistical setting. While TV regularization
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22.04.2021

Multiple Haplotype Reconstruction from Allele Frequency Data

Authors Pelizzola M, Behr M, Li H, Munk A, Futschik A Journal Nature Computational Science Citation Nat Comput Sci 1, 262–271 (2021). Abstract Because haplotype information is of widespread interest in biomedical applications, effort has been put into their reconstruction. Here, we propose an efficient method, called haploSep, that is
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09.04.2021

Analysis of patchclamp recordings: model-free multiscale methods and software

Authors Pein F, Eltzner B, Munk A Journal European Biophysics Journal Citation Eur Biophys J. 2021 Apr 9. Abstract Analysis of patchclamp recordings is often a challenging issue. We give practical guidance how such recordings can be analyzed using the model-free multiscale idealization methodology JSMURF, JULES, and HILDE. We provide
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