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Publications since 2020
| F. Altekrüger, A. Denker, P. Hagemann, J. Hertrich, P. Maass and G. Steidl, PatchNR: Learning from Small Data by Patch Normalizing Flow Regularization ArXiv Preprint 2205.12021, submitted. |
| D.P.L. Nguyen, J. Hertrich, J.-F. Aujol and Y. Berthoumieu, Image super-resolution with PCA reduced generalized Gaussian mixture models HAL preprint hal-03664839, submitted. |
| J. von Lindheim Simple Approximative Algorithms for Free-Support Wasserstein Barycenters ArXiv preprint 2203.05267, submitted. |
| F. Altekrüger and J. Hertrich, WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution ArXiv preprint 2201.08157, submitted. |
| P. Hagemann, J. Hertrich and G. Steidl, Generalized Normalizing Flows via Markov Chains ArXiv preprint 2111.12506, 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. |
| 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 |
| 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. |
| P. Hagemann, J. Hertrich and G. Steidl, Stochastic normalizing flows for inverse problems: A markov chain viewpoint SIAM/ASA Journal on Uncertainty Quantification, accepted. |
| G. Steidl and M. Winkler, A new constrained model for solving the nonsymmetric inverse stochastic eigenvalue problem Linear and Multilinear Algebra, 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. |
| A. Berdellima and G. Steidl, On alpha-firmly nonexpansive operators in r-uniformly convex spaces Results in Mathematics, accepted. |
| J. Hertrich and G. Steidl, Inertial stochastic PALM and its application for learning Student-t mixture models Sampling Theory, Signal Processing, and Data Analysis, vol. 20, no. 4. |
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| S. Mildenberger and M. Quellmalz, Approximation Properties of the Double Fourier Sphere Method in Journal of Fourier Analysis and Applications 28, Article number: 31, 2022. |
| 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, vol. 16, pp. 341-366. |
| 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 56, p. 123-149. |
| J. Hertrich, F. Ba and G. Steidl Sparse Mixture Models Inspired by ANOVA Decompositions Electronic Transactions on Numerical Analysis, vol. 55, pp. 142-168. |
| 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 37, 115002. |
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| 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. |
| P. Hagemann, S. Neumayer Stabilizing Invertible Neural Networks Using Mixture Models Inverse Problems. |
| 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. |
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| 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. |
| 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. |