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Publications since 2020

F. Altekrüger and J. Hertrich,
WPPNets: Unsupervised CNN Training with Wasserstein Patch Priors for Image Superresolution
ArXiv preprint 2201.08157, submitted.
F. Beier, J. von Lindheim, S. Neumayer and G. Steidl,
Unbalanced multi-marginal optimal transport
ArXiv preprint 2103.10854, submitted.
A. Berdellima, R. Beinert, M. Gräf and G. Steidl,
On the dynamical system of principal curves in rd
ArXiv preprint 2108.00227, submitted.

P. Hagemann, J. Hertrich and G. Steidl,
Stochastic normalizing flows for inverse problems: A markov chain viewpoint
ArXiv preprint 2109.11375, submitted.

J. Hertrich and G. Steidl,
Inertial stochastic PALM and its application for learning Student-t mixture models
ArXiv preprint 2005.02204, submitted.

A. Bërdëllima,
Compact sets and the closure of their convex hulls in CAT(0) spaces.
ArXiv preprint 2109.06002
, submitted.

A. Bërdëllima,
On a theorem about Mosco convergence in Hadamard spaces
ArXiv preprint 2010.05554
, submitted.

F. Faucher, C. Kirisits, M. Quellmalz, O. Scherzer, E. Setterqvist
Diffraction Tomography, Fourier Reconstruction, and Full Waveform Inversion
ArXiv preprint 2110.07921

S. Mildenberger, M. Quellmalz
Approximation properties of the double Fourier sphere method
ArXiv preprint 2108.05662

J. Hertrich, A. Houdard and C. Redenbach
Wasserstein Patch Prior for Image Superresolution
arXiv Preprint 2109.12880, submitted.

R. Beinert
Approximation of Curve-based Sleeve Functions in High Dimensions
arXiv Preprint 2109.06726, submitted.

G. Steidl and M. Winkler,
A new constrained model for solving the nonsymmetric inverse stochastic eigenvalue problem
Linear and Multilinear Algebra, accepted.

C. Kirisits, M. Quellmalz, M. Ritsch-Marte, O. Scherzer, E. Setterqvist and G. Steidl,
Fourier reconstruction for diffraction tomography of an object rotated into arbitrary orientations
Inverse Problems, accepted.

J. Hertrich, D. P. L. Nguyen, J.-F. Aujol, D. Bernard, Y. Berthoumieu, A. Saadaldin and G. Steidl,
PCA reduced Gaussian mixture models with application in superresolution
Inverse Problems and Imaging, accepted.

J. Hertrich, S. Neumayer and G. Steidl,
Convolutional proximal neural networks and plug-and-play algorithms
Linear Algebra and its Applications, accepted.

M. Gräf, S. Neumayer, R. Hielscher, G. Steidl, M. Liesegang and T. Beck,
An optical flow model in electron backscatter diffraction
SIAM Journal on Imaging Sciences, accepted.

S. Dahlke, F. D. Mari, E. D. Vito, M. Hansen, M. Hasannasab, M. Quellmalz, G. Steidl and G. Teschke,
Continuous wavelet frames on the sphere: The group-theoretic approach revisited
Applied and Computational Harmonic Analysis, accepted.

A. Berdellima and G. Steidl,
On alpha-firmly nonexpansive operators in r-uniformly convex spaces
Results in Mathematics, accepted.

J. Hertrich, F. Ba and G. Steidl
Sparse Mixture Models Inspired by ANOVA Decompositions
Electronic Transactions on Numerical Analysis, accepted.

Publications 2021
A. Andrele, N. Fachmin, P. Hagemann, V. Soltewisch and G. Steidl,
Invertible neural networks versus mcmc for posterior reconstruction in gazing incidence X-ray fluorescence
in Scale Space and Variational Methods in Computer Vision, A. Elmoataz, J. fadili, Y. Quéau, R. Rabin and L. Simon, Eds., ser. LNCS 12679, 2021, pp. 528–539.
R. Beinert and G. Steidl,
Robust PCA via regularized reaper with a matrix-free proximal algorithm
Journal of Mathematical Imaging and Vision, vol. 63, pp. 626–649, 2021.

P. Koltai, J. von Lindheim, S. Neumayer, G. Steidl,
Transfer Operators from Optimal Transport Plans for Coherent Set Detection
Physica D: Nonlinear Phenomena, vol. 426, Paper No. 132980.
O. Christensen, M. Hasannasab and G. Steidl,
On approximate operator representations of sequences in Banach spaces
Complex Analysis and Operator Theory, vol. 15, no. 3, 2021.

M. Ehler, M. Gräf, S. Neumayer and G. Steidl,
Curve based approximation of measures on manifolds by discrepancy minimization
Foundations in Computational Mathematics, 2021.

C. Hartman, H. A. Weiss, P. Lechner, W. Volk, S. Neumayer, J. H. Fitschen and G. Steidl
Measurement of strain, strain rate and crack evolution in shear cutting
Journal of Materials Processing Technology, vol. 288, p. 116 872, 2021.

M. Hasanasab, J. Hertrich, F. Laus and G. Steidl,
Alternatives of the EM algorithm for estimating the parameters of the Student-t distribution
Numerical Algorithms, vol. 87, pp. 77–118, 2021.

S. Neumayer and G. Steidl,
From optimal transport to discrepancy
in Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging, Springer, 2021.

C. B. Schoenlieb, H. Zhao, G. Steidl and M. B. Watkin
Principles and trends in mathematical imaging
SIAM News, vol. March, 2021.

R. Beinert, P. Jung, G. Steidl, T. Szollmann
Super-resolution for doubly-dispersive channel estimation
Journal of Sampling Theory, Signal Processing, and Data Analysis, 19(16), 1-36, 2021.

R. Beinert, K. Bredies
Tensor-free proximal methods for lifted bilinear/quadratic inverse problems with applications to phase retrieval
Foundations of Computational Mathematics, 21, 1181-1232, 2021

R. Beinert, M. Hasannasab
Phase Retrieval via Polarization in Dynamical Sampling
In: A. Elmoataz, J. Fadili, Y. Quéau, J. Rabin, L. Simon (Hrsg.)
Scale Space and Variational Methods in Computer Vision. SSVM 2021
Cham : Springer, 2021 (Lecture Notes in Computer Science 12679 ), 516–527.

A. Bërdëllima, F. Lauster and D. R. Luke
α-Firmly Nonexpansive Operators in Metric Spaces.
Journal of Fixed Point Theory Applications

A. Bërdëllima
On a notion of averaged mappings in CAT(0) spaces.

Funct. Anal. Its Appl.
A. Bërdëllima,
Duopoly price competition with limited capacity. 
Econ. Theory Bull.
 9, 143–154

Ole Christensen, Marzieh Hasannasab
Completion versus removal of redundancy by perturbation
Canadian Mathematical Bulletin.

J. Hertrich, S. Neumayer and G. Steidl
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms
Linear Algebra and its Applications, vol 631, pp. 203-234.

J. Hertrich, D. P. L. Nguyen, J.-F. Aujol, D. Bernard, Y. Berthoumieu, A. Saadaldin and G. Steidl
PCA reduced Gaussian mixture models with application in superresolution
Inverse Problems and Imaging.

P. Hagemann, S. Neumayer
Stabilizing Invertible Neural Networks Using Mixture Mod
Inverse Problems.

Publications 2020
T. Batard, J. Hertrich and G. Steidl,
Variational models for color image correction inspired by visual perception and neuroscience
Journal of Mathematical Imaging and Vision, vol. 62, no. 9, pp. 1173–1194, 2020.

R. H. Chan, A. Cohen, J. Fadili, A. Hero and G. Steidl, Guest editorial: Special issue in memory of mila nikolova, Journal of Mathematical Imaging and Vision, vol. 62, 2020.
M. Hasannasab, J. Hertrich, S. Neumayer, G. Plonka, S. Setzer and G. Steidl Parseval proximal neural networks
The Journal of Fourier Analysis and its Applications, vol. 26, pp. 1–31, 2020.

D. Havenstein, P. Lysakovski, N. May, G. Moerkotte and G. Steidl
Fast entropy maximization for selectivity estimation of conjunctive predicates on CPUs and GPUs,
Proceedings of the 23rd International Conference on Extending Database Technology (EDBT), 2020, pp. 1–9.

S. Neumayer, M. Nimmer, S. Setzer and G. Steidl
On the rotational invariant l1-norm PCA
Linear Algebra and its Applications, vol. 587, pp. 243–270, 2020.

M. Bacak, J. Hertrich, S. Neumayer and G. Steidl
Minimal Lipschitz and inftinity–harmonic extensions of vector-valued functions on finite graphs
Information and Inference: A Journal of the IMA, vol. 9, no. 4, pp. 935–959, 2020.

S. Neumayer, M. Nimmer, S. Setzer and G. Steidl
On the robust PCA and Weiszfeld’s algorithm
Applied Mathematics and Optimization, vol. 82, pp. 1017–1048, 2020.

R. Beinert, G. Plonka
One-Dimensional Discrete-Time Phase Retrieval
In: T. Salditt, A. Egner, D. R. Luke (Hrsg.)
Nanoscale Photonic Imaging
Cham : Springer, 2020 (Topics in Applied Physics 134), Kapitel 24, 603-627.

M. Quellmalz
The Funk-Radon transform for hyperplane sections through a common point
Analysis and Mathematical Physics 10(38), 2020.
M. Hasannasab, J. Hertrich, F. Laus and G. Steidl
Alternatives to the EM Algorithm for ML-Estimation of Location, Scatter Matrix and Degree of Freedom of the Student-t Distribution
Numerical Algorithms, vol. 87, pp. 77-118.

A. Effland, S. Neumayer, M. Rumpf
Convergence of the Time Discrete Metamorphosis Model on Hadamard Manifolds
SIAM Journal on Imaging Sciences. 13(2):557–588.

L. Lang, S. Neumayer, O. Öktem, C. B. Schönlieb
Template-Based Image Reconstruction from Sparse Tomographic Data
Applied Mathematics and Optimization. 82:1081-1109.










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