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Publications of WG Industrial Mathematics

Monographies (4)

H. Bock, K. Küfer, P. Maaß, A. Milde, V. Schulz (Eds.).
German Success Stories in Industrial Mathematics .
Mathematics in Industrie, 167 pages, Springer Verlag, 2022.
DOI: 10.1007/978-3-030-81455-7
R. Dahlhaus, J. Kurths, P. Maaß, J. Timmer (Eds.).
Mathematical Methods in Time Series Analysis and Digital Image Processing.
Understanding Complex Systems, 294 pages, Springer Verlag, 2008.
A. K. Louis, P. Maaß, A. Rieder.
Wavelets. Theorie und Anwendungen.
Studienbücher Mathematik, 330 pages, Teubner Verlag, 1998.
A. K. Louis, P. Maaß, A. Rieder.
Wavelets: Theory and Applications.
Pure and Applied Mathematics, 342 pages, WILEY-VCH, 1997.

Articles (220)

D. Erzmann, S. Dittmer.
Equivariant Neural Operators for gradient-Consistent Topology Optimization .
Journal of Computational Design and Engineering, 11(3):91-100, 2024.
DOI: 10.1093/jcde/qwae039
F. Altenkrüger, A. Denker, P. Hagemann, P. Maaß, G. Steidl.
PatchNR: Learning from Very Few Images by Patch Normalizing Flow Regularization.
Inverse Problems, 39(6), 2023.
online at: https://iopscience.iop.org/article/10.1088/1361-6420/acce5e/meta
D. Nganyu Tanyu, J. Ning, T. Freudenberg, N. Heilenkötter, A. Rademacher, U. Iben, P. Maaß.
Deep learning methods for partial differential equations and related parameter identification problems.
Inverse Problems, 39(10), 2023.
DOI: 10.1088/1361-6420/ace9d4
D. Erzmann, S. Dittmer, H. Harms, P. Maaß.
DL4TO: A Deep Learning Library for Sample-Efficient Topology Optimization.
Lecture Notes in Computer Science, Geometric Science of Information. GSI 2023 14071, Springer Verlag, 2023.
DOI: 10.1007/978-3-031-38271-0_54
J. Gödeke, G. Rigaud.
Imaging based on Compton scattering: model uncertainty and data-driven reconstruction methods.
Inverse Problems, 39(3), 2023.
DOI: 10.1088/1361-6420/acb2ed
C. Arndt, A. Denker, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, P. Maaß, J. Nickel.
Invertible residual networks in the context of regularization theory for linear inverse problems.
Inverse Problems, 39(12), IOPscience, 2023.
DOI: 10.1088/1361-6420/ad0660
online at: https://iopscience.iop.org/article/10.1088/1361-6420/ad0660
C. Arndt, A. Denker, S. Dittmer, J. Leuschner, J. Nickel, M. Schmidt.
Model-based deep learning approaches to the Helsinki Tomography Challenge 2022.
Applied Mathematics for Modern Challenges, 1(2), 2023.
DOI: 10.3934/ammc.2023007
S. Dittmer, M. Roberts, J. Gilbey, A. Biguri, .. AIX-COVNET Collaboration, J. Preller, J. H. F. Rudd, J. A. D. Aston, C. Schönlieb.
Navigating the development challenges in creating complex data systems.
nature machine intelligence, 5:681-686, Springer Verlag, 2023.
DOI: 10.1038/s42256-023-00665-x
online at: https://www.nature.com/articles/s42256-023-00665-x#citeas
A. Denker, I. Singh, R. Barbano, Z. Kereta, B. Jin, K. Thielemans, P. Maaß, S. Arridge.
Score-Based Generative Models for PET Image Reconstruction.
Erscheint in Machine Learning for Biomedical Imaging
online at: https://arxiv.org/abs/2308.14190
T. Shadbahr, M. Roberts, J. Stanczuk, J. Gilbey, P. Teare, S. Dittmer, M. Thorpe, R. V. Torne, E. Sala, P. Lio, M. Patel, .. AIX-COVNET Collaboration, J. H. F. Rudd, T. Mirtti, A. Rannikko, J. A. D. Aston, J. Tang, C. Schönlieb.
The impact of imputation quality on machine learning classifiers for datasets with missing values.
Communication medicine, 3, Springer Verlag, 2023.
DOI: 10.1038/s43856-023-00356-z
online at: https://www.nature.com/articles/s43856-023-00356-z#citeas
J. Antorán, R. Barbano, J. Leuschner, J. M. Hernández-Lobato, B. Jin.
Uncertainty Estimation for Computed Tomography with a Linearised Deep Image Prior.
Transactions on Machine Learning Research, 12, 2023.
online at: https://openreview.net/forum?id=FWyabz82fH
R. Barbano, J. Leuschner, M. Schmidt, A. Denker, A. Hauptmann, P. Maaß, B. Jin.
An Educated Warm Start For Deep Image Prior-based Micro CT Reconstruction.
IEEE Transactions on Computational Imaging, 8:1210-1222, 2022.
DOI: 10.1109/TCI.2022.3233188
S. Dittmer, C. Schönlieb, P. Maaß.
Ground Truth Free Denoising by Optimal Transport.
Erscheint in Numerical Algebra, Control, and Optimization
online at: https://arxiv.org/abs/2007.01575
C. Arndt, A. Denker, J. Nickel, J. Leuschner, M. Schmidt, G. Rigaud.
In Focus - hybrid deep learning approaches to the HDC2021 challenge.
Inverse Problems and Imaging, , 2022.
DOI: 10.3934/ipi.2022061
S. Arridge, P. Fernsel, A. Hauptmann.
Joint Reconstruction and Low-Rank Decomposition for Dynamic Inverse Problems.
Inverse Problems and Imaging, 16(3):483-523, 2022.
DOI: 10.3934/ipi.2021059
D. Nganyu Tanyu, D. Schulz, T. Tatietse, T. Lukong.
Long Term Electricity Load Forecast Based on Machine Learning for Cameroon’s Power System.
Energy and Environment Research, 12(1), 2022.
DOI: 10.5539/eer.v12n1p45
online at: https://ccsenet.org/journal/index.php/eer/article/view/0/47276
H. Albers, T. Knopp, M. Möddel, M. Boberg, T. Kluth.
Modeling the magnetization dynamics for large ensembles of immobilized magnetic nanoparticles in multi-dimensional magnetic particle imaging.
Journal of Magnetism and Magnetic Materials, 543, 168534, Elsevier, 2022.
DOI: 10.1016/j.jmmm.2021.168534
C. Arndt.
Regularization Theory of the Analytic Deep Prior Approach.
Inverse Problems, 38(11), 2022.
DOI: 10.1088/1361-6420/ac9011
C. Janßen, T. Boskamp, L. Hauberg-Lotte, J. Behrmann, S. Deininger, M. Kriegsmann, K. Kriegsmann, G. Steinbuß, H. Winter, T. Muley, R. Casadonte, J. Kriegsmann, P. Maaß.
Robust subtyping of non-small cell lung cancer whole sections through MALDI mass spectrometry imaging.
Proteomics - Clinical Applications, PRCA2208 , 2022.
DOI: 10.1002/prca.202100068
H. Albers, T. Kluth, T. Knopp.
Simulating magnetization dynamics of large ensembles of single domain nanoparticles: Numerical study of Brown/Néel dynamics and parameter identification problems in magnetic particle imaging.
Journal of Magnetism and Magnetic Materials, 541, 168508, Elsevier, 2022.
DOI: 10.1016/j.jmmm.2021.168508
online at: https://www.sciencedirect.com/science/article/abs/pii/S0304885321007678
M. Beckmann, A. Bhandari, F. Krahmer.
The Modulo Radon Transform: Theory, Algorithms and Applications.
SIAM Journal on Imaging Sciences, 15(2):455-490, 2022.
DOI: 10.1137/21M1424615
G. Rigaud.
3D Compton scattering imaging with multiple scattering: analysis by FIO and contour reconstruction.
Inverse Problems, 37(6), 2021.
online at: https://iopscience.iop.org/article/10.1088/1361-6420/abf22b
S. Schulze, J. Leuschner, E. King.
Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients.
MDPI Open Access Journals Signals, 2(4):637-661, 2021.
DOI: 10.3390/signals2040039
online at: https://www.mdpi.com/2624-6120/2/4/39
A. Denker, M. Schmidt, J. Leuschner, P. Maaß.
Conditional Invertible Neural Networks for Medical Imaging .
MDPI Journal of Imaging, Inverse Problems and Imaging 7(11), 243 pp., 2021.
DOI: 10.3390/jimaging7110243
T. Boskamp, R. Casadonte, L. Hauberg-Lotte, S. Deininger, J. Kriegsmann, B. Maass.
Cross-Normalization of MALDI Mass Spectrometry Imaging Data Improves Site-to-Site Reproducibility.
Analytical Chemistry, 93(30):10584-10592, 2021.
online at: https://doi.org/10.1021/acs.analchem.1c01792
S. Dittmer, T. Kluth, M. Henriksen, P. Maaß.
Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset.
International Journal on Magnetic Particle Imaging, 7(1), 2021.
online at: https://journal.iwmpi.org/index.php/iwmpi/article/view/148
J. Le Clerc Arrastia, N. Heilenkötter, D. Otero Baguer, L. Hauberg-Lotte, T. Boskamp, S. Hetzer, N. Duschner , J. Schaller , P. Maaß.
Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma.
MDPI Journal of Imaging, 71 7(4), Meisenbach Verlag, Bamberg, 2021.
DOI: 10.3390/jimaging7040071
M. Möddel, F. Griese, T. Kluth, T. Knopp.
Estimating the Spatial Orientation of Immobilized Magnetic Nanoparticles with Parallel-Aligned Easy Axes.
Physical Review Applied, 16(4), L041003 pp., 2021.
J. Leuschner, M. Schmidt, D. Otero Baguer, P. Maaß.
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction.
Scientific Data, 8(109), 2021.
DOI: 10.1038/s41597-021-00893-z
L. Kuger, G. Rigaud.
Modeling and Reconstruction Strategy for Compton Scattering Tomography with Scintillation Crystals.
Crystals, 11(6), 2021.
DOI: https://doi.org/10.3390/cryst11060641
J. Leuschner, M. Schmidt, P. Ganguly, V. Andriiashen, S. Coban, A. Denker, D. Bauer, A. Hadjifaradji, K. Batenburg, B. Maass, M. von Eijnatten.
Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications.
MDPI Journal of Imaging, 7(3), 44 pp., 2021.
DOI: 10.3390/jimaging7030044
online at: https://www.mdpi.com/2313-433X/7/3/44
P. Fernsel.
Spatially Coherent Clustering Based on Orthogonal Nonnegative Matrix Factorization.
MDPI Journal of Imaging, 7(10), 2021.
DOI: 10.3390/jimaging7100194
online at: https://www.mdpi.com/2313-433X/7/10/194
O. Klein, F. Fogt, S. Hollerbach, G. Nebrich, T. Boskamp, A. Wellmann.
Classification of Inflammatory Bowel Disease from Formalin‐Fixed, Paraffin‐Embedded Tissue Biopsies via Imaging Mass Spectrometry.
Proteomics - Clinical Applications, 190131 , Wiley, 2020.
DOI: 10.1002/prca.201900131
D. Otero Baguer, J. Leuschner, M. Schmidt.
Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods.
Inverse Problems, 36(9), IOPscience, 2020.
DOI: 10.1088/1361-6420/aba415
M. Beckmann, P. Maaß, J. Nickel.
Error analysis for filtered back projection reconstructions in Besov spaces.
Inverse Problems, 37 014002 37(1), IOPscience, 2020.
T. Kluth, C. Bathke, M. Jiang, P. Maaß.
Joint super-resolution image reconstruction and parameter identification in imaging operator: Analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging.
Inverse Problems, 36(12), 2020.
DOI: https://doi.org/10.1088/1361-6420/abc2fe
T. Kluth, B. Jin.
L1 data fitting for robust reconstruction in magnetic particle imaging: quantitative evaluation on Open MPI dataset.
International Journal on Magnetic Particle Imaging, , 2020.
DOI: 10.18416/IJMPI.2020.2012001
online at: https://journal.iwmpi.org/index.php/iwmpi/article/view/146
T. H. Nguyen, D. Nho Hào, P. Maaß, L. Colombi Ciacchi.
Mathematical aspects of catalyst positioning in lithium/air batteries.
Inverse Problems, 36(4), 2020.
DOI: 10.1088/1361-6420/ab47e6
F. Lieb, T. Boskamp, H. Stark.
Peak detection for MALDI mass spectrometry imaging data using sparse frame multipliers.
Journal of Proteomics, 103852 225, Elsevier, 2020.
DOI: 10.1016/j.jprot.2020.103852
T. Kluth.
Recent developments on system function/matrix representation, hybrid simulation techniques, and magnetic actuation.
International Journal on Magnetic Particle Imaging, 6(1), 2020.
DOI: https://journal.iwmpi.org/index.php/iwmpi/article/view/327
G. Rigaud, B. Hahn.
Reconstruction Algorithm For 3D Compton Scattering Imaging With Incomplete Data.
Erscheint in Inverse Problems in Science and Engineering
S. Dittmer, T. Kluth, P. Maaß, D. Otero Baguer.
Regularization by architecture: A deep prior approach for inverse problems.
Journal of Mathematical Imaging and Vision, 62(3):456-470, Springer Verlag, 2020.
DOI: 10.1007/s10851-019-00923-x
online at: http://link.springer.com/article/10.1007/s10851-019-00923-x
T. Kluth, H. Albers.
Simulation of non-linear magnetization effects and parameter identification problems in magnetic particle imaging.
Erscheint in Oberwolfach Reports
T. Boskamp, D. Lachmund, R. Casadonte, L. Hauberg-Lotte, J. H. Kobarg, J. Kriegsmann, P. Maaß.
Using the chemical noise background in MALDI mass spectrometry imaging for mass alignment and calibration.
Analytical Chemistry, 92(1):1301-1308, 2020.
DOI: 10.1021/acs.analchem.9b04473
online at: https://doi.org/10.1021/acs.analchem.9b04473
J. Clemens, T. Kluth, T. Reineking.
β - SLAM: Simultaneous Localization an Grid Mapping with Beta Distributions.
Information Fusion, 52:62-75, Elsevier, 2019.
DOI: 10.1016/j.inffus.2018.11.005
T. Kluth, B. Jin.
Enhanced Reconstruction in Magnetic Particle Imaging by Whitening and Randomized SVD Approximation.
Physics in Medicine and Biology, Article ID 125026 64(12), 2019.
DOI: 10.1088/1361-6560/ab1a4f
A. Ardestani, S. Li, K. Annamalai, B. Lupse, S. Geravandi, A. Dobrowolski, S. Yu, S. Zhu, T. D. Baguley, M. Surakattula, J. Oetjen, L. Hauberg-Lotte, R. Herranz, S. Awal, D. Altenhofen, V. Nguyen-Tran, S. Joseph, P. G. Schultz, A. K. Chatterjee, N. Rogers, M. S. Tremblay, W. Shen, K. Maedler.
Neratinib protects pancreatic beta cells in diabetes.
Nature Communications, 10(5015), 2019.
DOI: 10.1038/s41467-019-12880-5.
online at: https://doi.org/10.1038/s41467-019-12880" target="doi">015 | https://doi.org/10.1038/s41467-019-12880
S. Dittmer, E. King, P. Maaß.
Singular values for ReLU layers.
IEEE Transactions on Neural Networks and Learning Systems, Article , 2019.
online at: https://ieeexplore.ieee.org/document/8891761
S. Arridge, P. Maaß, O. Öktem, C. Schönlieb.
Solving inverse problems using data-driven models.
Acta Numerica, 28:pp. 1-174, Cambridge University Press, 2019.
DOI: 10.1017/S0962492919000059
T. Kluth, P. Szwargulski, T. Knopp.
Towards Accurate Modeling of the Multidimensional Magnetic Particle Imaging Physics.
New Journal of Physics, Article ID 10303 21, 10 pp., 2019.
online at: https://iopscience.iop.org/article/10.1088/1367-2630/ab4938/pdf
J. Quanico, L. Hauberg-Lotte, S. Devaux, Z. Laouby, C. Mériaux, A. Raffo-Romero, M. Rose, L. . Westerheide, J. Vehmeyer, F. Rodet, P. Maaß, D. Cizkova, N. Zilka, V. Cubinkova, I. Fournier, M. Salzet.
3D MALDI mass spectrometry imaging reveals specific localization of long-chain acylcarnitines within a 10-day time window of spinal cord injury.
Scientific Reports, 8(16083), 2018.
DOI: 10.1038/s41598-018-34518-0
P. Fernsel, P. Maaß.
A Survey on Surrogate Approaches to Non-negative Matrix Factorization.
Vietnam Journal of Mathematics, 46(4):987-1021, Springer Verlag, 2018.
DOI: 10.1007/s10013-018-0315-x
J. Behrmann, C. Etmann, T. Boskamp, R. Casadonte, J. Kriegsmann, P. Maaß.
Deep Learning for Tumor Classification in Imaging Mass Spectrometry.
Bioinformatics, 34(7):1215-1223, Oxford University Press, 2018.
DOI: 10.1093/bioinformatics/btx724
T. Kluth.
Mathematical models for magnetic particle imaging.
Inverse Problems, 34(8), 2018.
DOI: 10.1088/1361-6420/aac535
T. Kluth, B. Jin, G. Li.
On the Degree of Ill-Posedness of Multi-Dimensional Magnetic Particle Imaging.
Inverse Problems, 34(9), 2018.
DOI: 10.1088/1361-6420/aad015
J. Leuschner, M. Schmidt, P. Fernsel, D. Lachmund, T. Boskamp, P. Maaß.
Supervised Non-negative Matrix Factorization Methods for MALDI Imaging Applications.
Bioinformatics, bty909 , 2018.
DOI: 10.1093/bioinformatics/bty909
Y. Cordero Hernandez, T. Boskamp, R. Casadonte, L. Hauberg-Lotte, J. Oetjen, D. Lachmund, A. Peter, D. Trede, K. Kriegsmann, M. Kriegsmann, J. Kriegsmann, P. Maaß.
Targeted Feature Extraction in MALDI Mass Spectrometry Imaging to Discriminate Proteomic Profiles of Breast and Ovarian Cancer.
Proteomics - Clinical Applications, 1700168 , Wiley, 2018.
DOI: 10.1002/prca.201700168
N. Hase, S. M. Miller, P. Maaß, J. Notholt, M. Palm, T. Warneke.
Atmospheric Inverse Modeling via Sparse Reconstruction.
Geoscientific Model Development (GMD), 10:3695-3713, 2017.
DOI: 10.5194/gmd-10-3695-2017
C. Bathke, T. Kluth, C. Brandt, P. Maaß.
Improved image reconstruction in magnetic particle imaging using structural a priori information.
International Journal on Magnetic Particle Imaging, Article ID 1703015, 3(1), 10 pages, 2017.
DOI: 10.18416/ijmpi.2017.1703015
T. Kluth, P. Maaß.
Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction.
International Journal on Magnetic Particle Imaging, Article ID 1707004 3(2), 10 pages, 2017.
DOI: 10.18416/ijmpi.2017.1707004
J. Nüße, M. Waespy, U. Mirastschijski, J. Oetjen, N. Brandes, O. Rebello, F. Paroni, S. Kelm, F. Dietz.
Two new isoforms of the human hepatoma-derived growth factor interact with components of the cytoskeleton.
Biological Cemistry, 397(5), 417–436 pp., 2016.
DOI: 10.1515/hsz-2015-0273
T. Boskamp, D. Lachmund, J. Oetjen, Y. Hernandez-Cordero, D. Trede, P. Maaß, R. Casadonte, J. Kriegsmann, A. Warth, H. Dienemann, W. Weichert, M. Kriegsmann.
A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.
BBA - Proteins and Proteomics, , 2016.
DOI: 10.1016/j.bbapap.2016.11.003
K. Kazimierski, I. Piotrowska-Kurczewski, F. Böhmermann, O. Riemer.
A statistical filtering method for denoising of micro-force measurements.
The International Journal of Advanced Manufacturing Technology, , 1693–1704, Springer Verlag, 2016.
DOI: 10.1007/s00170-016-8513-8
online at: http://link.springer.com/article/10.1007/s00170-016-8513-8
J. Oetjen, D. Lachmund, A. Palmer, F. Alexandrov, M. Becker, T. Boskamp, P. Maaß.
An approach to optimize sample preparation for MALDI imaging MS of FFPE sections using fractional factorial design of experiments.
Analytical and Bioanalytical Chemistry, 408(24):6729-40, 2016.
DOI: 10.1007/s00216-016-9793-4
P. Maaß, R. Strehlow.
An iterative regularization method for nonlinear problems based on Bregman projections.
Inverse Problems, Article ID 115013 32(11), 20 pages, 2016.
Ausgezeichnet als Highlight Paper

DOI: 10.1088/0266-5611/32/11/115013
Q. M. Pham, D. Nho Hào, P. Maaß, M. Pidcock.
Descent Gradient Methods for Nonsmooth Minimization Problems and Applicatons to Ill-Posed Problems.
Journal of Computational and Applied Mathematics, 298:105-122, 2016.
DOI: 10.1016/j.cam.2015.11.039
F. Hoffmann, J. M. Lotz, J. Lotz, S. Heldmann, D. Trede, J. Oetjen, M. Becker, G. Ernst, P. Maaß, F. Alexandrov, O. Guntinas-Lichius, H. Thiele, F. von Eggeling.
Integration of 3D multimodal imaging data of a head and neck cancer and advanced feature recognition.
BBA - Proteins and Proteomics, , 2016.
DOI: 10.1016/j.bbapap.2016.08.018
S. Devaux, D. Cizkova, J. Quanico, J. Franck, S. Nataf, L. Pays, L. Hauberg-Lotte, P. Maaß, J. H. Kobarg, F. Kobeissy, C. Mériaux, M. Wisztorski, L. Slovinska, J. Blasko, V. Cigankova, I. Fournier, M. Salzet.
Proteomic Analysis of the Spatio-temporal Based Molecular Kinetics of Acute Spinal Cord Injury Identifies a Time- and Segment-specific Window for Effectife Tissue Repair.
Molecular & Cellular Proteomics, 15:2641-2670, 2016.
DOI: 10.1074/mcp.M115.057794
A. Egozi, D. Eilot, P. Maaß, C. Sagiv.
A robust estimation method for camera calibration with known rotation.
Applied Mathematics, 6(9):1538-1552 , 2015.
DOI: 10.4236/am.2015.69137
J. Oetjen, K. Veselkov, J. Watrous, J. McKenzie, M. Becker, L. Hauberg-Lotte, J. H. Kobarg, A. K. Mróz, N. Strittmatter, F. Hoffmann, D. Trede, A. Palmer, S. Schiffler, K. Steinhorst, M. Aichler, R. Goldin, O. Guntinas-Lichius, F. von Eggeling, H. Thiele, K. Mädler, A. Walch, P. Maaß, P. C. Dorrestein, Z. Takats, F. Alexandrov.
Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry.
GigaScience, 4, 2015.
DOI: 10.1186/s13742-015-0059-4
C. Song, M. Mazzola, X. Cheng, J. Oetjen, F. Alexandrov, P. C. Dorrestein, J. Watrous, M. van der Voort, J. M. Raaijmakers.
Molecular and chemical dialogues in bacteria-protozoa interactions.
Scientific Reports, Article ID 12837 5, 2015.
DOI: 10.1038/srep12837
T. Dabrowski, A. Struck, D. Fenske, P. Maaß, L. Colombi Ciacchi.
Optimization of Catalytically Active Sites Positioning in Porous Cathodes of Lithium/Air Batteries Filled with Different Electrolytes.
Journal of The Electrochemical Society, 162(14):A2796-A2804, 2015.
DOI: 10.1149/2.0861514jes
I. Piotrowska-Kurczewski, J. Vehmeyer, P. Gralla, F. E. Elsner-Dörge, F. Böhmermann, O. Riemer, P. Maaß.
Reduzierung der Formabweichung beim Mikrofräsen.
Tagungsband 7. Kolloquium Mikroproduktion, ISBN: 978-3-00-050-755-7 , 23–30 pp., 2015.
C. Bockelmann, H. Schepker, A. Dekorsy, A. Bartels, D. Trede, K. Kazimierski.
C-Curve: A Finite Alphabet based Parameter Choice Rule for Elastic-Net in Sporadic Communication.
IEEE Communication Letters, 18(8):1443 -- 1446, 2014.
DOI: 10.1109/LCOMM.2014.2329487
H. Thiele, S. Heldmann, D. Trede, J. Strehlow, S. Wirtz, W. Dreher, J. Berger, J. Oetjen, J. H. Kobarg, B. Fischer, P. Maaß.
2D and 3D MALDI-Imaging: Conceptual Strategies for Visualization and Data Mining.
BBA - Proteins and Proteomics, 1844(1):117-137, 2014.
DOI: 10.1016/j.bbapap.2013.01.040
G. Ernst, O. Guntinas-Lichius, L. Hauberg-Lotte, D. Trede, M. Becker, F. Alexandrov, F. von Eggeling.
Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix-assisted laser desorption ionization imaging and spatial segmentation.
Head & Neck, 37(7), 2014.
DOI: 10.1002/hed.23713
B. Denkena, J. Vehmeyer, D. Niederwestberg, P. Maaß.
Identification of the specific cutting force for geometrically defined cutting edges and varying cutting conditions.
International Journal of Machine Tools and Manufacture, 82:42-49, 2014.
DOI: 10.1016/j.ijmachtools.2014.03.009
O. Klein, K. Strohschein, G. Nebrich, J. Oetjen, D. Trede, H. Thiele, F. Alexandrov, P. Giavalisco, G. N. Duda, P. Roth von, S. Geissler, J. Klose, T. Winkler.
MALDI imaging mass spectrometry: Discrimination of pathophysiological regions in traumatized skeletal muscle by characteristic peptide signatures.
Proteomics, 14(20):2249-2260, 2014.
DOI: 10.1002/pmic.201400088
J. H. Kobarg, P. Maaß, J. Oetjen, O. Tropp, E. Hirsch, C. Sagiv, M. Goldabaee, P. Vandergheynst.
Numerical experiments with MALDI Imaging data.
Advances in Computational Mathematics, 40(3):667-682, 2014.
DOI: 10.1007/s10444-013-9325-0
R. M. M. Abed, L. Polerecky, A. Al-Habsi, J. Oetjen, M. Strous, D. de Beer.
Rapid Recovery of Cyanobacterial Pigments in Desiccated Biological Soil Crusts following Addition of Water.
PLoS ONE, , 2014.
DOI: 10.1371/journal.pone.0112372
M. Jiang, P. Maaß, T. Page.
Regularizing properties of the Mumford-Shah functional for imaging applications.
Inverse Problems, 30(3), 035007 , 2014.
Ausgezeichnet als Highlight Paper

DOI: 10.1088/0266-5611/30/3/035007
P. Maaß, C. Sagiv, H. Stark, B. Torresani.
Signal representation, uncertainty principles and localization measures.
Advances in Computational Mathematics, 40(3):597-607, Springer Verlag, 2014.
DOI: 10.1007/s10444-014-9341-8
M. Gehre, T. Kluth, C. Sebu, P. Maaß.
Sparse 3D reconstructions in electrical impedance tomography using real data.
Inverse Problems in Science and Engineering, 22(1):31-44, Taylor & Francis, 2014.
DOI: 10.1080/17415977.2013.827183
E. Herrholz, D. Lorenz, G. Teschke, D. Trede.
Sparsity and Compressed Sensing in Inverse Problems.
Lecture Notes in Computational Science and Engineering, 102:365-379, Springer Verlag, 2014.
DOI: 10.1007/978-3-319-08159-5_18
A. Bartels, P. Dülk, D. Trede, F. Alexandrov, P. Maaß.
Compressed sensing in imaging mass spectrometry.
Inverse Problems, 29(12), 125015 (24pp), IOPscience, 2013.
Selected as one of the highlights among all articles published in IOP "Inverse Problems" in 2013.

DOI: 10.1088/0266-5611/29/12/125015
C. M. Rath, J. Y. Yang, F. Alexandrov, P. C. Dorrestein.
Data-independent microbial metabolomics with ambient ionization mass spectrometry.
Journal of Mass Spectrometry, 24(8):1167-1176, 2013.
DOI: 10.1007/s13361-013-0608-y
V. M. Calo, N. Collier, M. Gehre, B. Jin, H. Radwan, M. Santillana.
Gradient-based estimation of Manning's friction coefficient from noisy data.
Journal of Computational and Applied Mathematics, 238:1-13, 2013.
DOI: 10.1016/j.cam.2012.08.004
I. Piotrowska-Kurczewski, J. Schlasche, D. Weimer, B. Scholz-Reiter, P. Maaß.
Image Denoising and Quality inspection of Micro Components using Perona-Malik Diffusion.
Procedia CIRP, 8:432-437, Elsevier, 2013.
DOI: 10.1016/j.procir.2013.06.129
F. Alexandrov.
Imaging mass spectrometry reveals modified forms of histone H4 as new biomarkers of microvascular invasion in hepatocellular carcinomas.
Hepatology, 58(3):983-94, 2013.
DOI: 10.1002/hep.26433
J. Watrous, F. Alexandrov, P. C. Dorrestein.
Interspecies interactions stimulate diversification of the Streptomyces coelicolor secreted metabolome.
mBio, 4(4):e00459-13, 2013.
DOI: 10.1128/mBio.00459-13
F. Alexandrov, P. E. . Bourne.
Learning how to run a lab: interviews with Principal Investigators.
POLS Computational Biology, 9(11), e1003349 pp., 2013.
DOI: 10.1371/journal.pcbi.1003349
S. Steurer, C. Borkowski, S. Odinga, M. Buchholz, C. Koop, H. Huland, M. Becker, M. Witt, D. Trede, M. Omidi, O. Kraus, A. S. Bahar, A. S. Seddiqi, J. M. Singer, M. Kwiatkowski, M. Trusch, R. Simon, M. Wurlitzer, S. Minner, T. Schlomm, G. Sauter, H. Schlüter.
MALDI mass spectrometric imaging based identification of clinically relevant signals in prostate cancer using large-scale tissue microarrays.
Erscheint in International Journal of Cancer
DOI: 10.1002/ijc.28080
J. Watrous, P. Roach, B. S. Heath, F. Alexandrov, J. Laskin, P. C. Dorrestein.
Metabolic Profiling Directly from the Petri Dish Using Nanospray Desorption Electrospray Ionization Imaging Mass Spectrometry.
Analytical Chemistry, 85(21), 10385–10391, 2013.
DOI: 10.1021/ac4023154
J. Watrous, F. Alexandrov, P. C. Dorrestein.
Microbial metabolic exchange in 3D.
ISME Journal, 7(4):770-780, 2013.
DOI: 10.1038/ismej.2012.155
J. Oetjen, M. Aichler, D. Trede, J. Strehlow, J. Berger, S. Heldmann, M. Becker, M. Gottschalk, J. H. Kobarg, S. Wirtz, S. Schiffler, H. Thiele, A. Walch, P. Maaß, F. Alexandrov.
MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation .
Journal of Proteomics, 90:52-60, 2013.
DOI: 10.1016/j.jprot.2013.03.013
F. Alexandrov, M. Becker, A. C. Crecelius.
Phenalenone-type phytoalexins mediate resistance of banana plants (Musa spp.) to the burrowing nematode Radopholus similis.
Proceedings of the National Academy of Sciences of the United States of America , , 2013.
DOI: 10.1073/pnas.1314168110
F. Alexandrov, P. Lasch.
Segmentation of Confocal Raman Microspectroscopic Imaging Data Using Edge-Preserving Denoising and Clustering.
Analytical Chemistry, 85(12):5676-83, 2013.
DOI: 10.1021/ac303257d
Q. M. Pham, D. Nho Hào, P. Maaß, M. Pidcock.
Semismooth Newton and Quasi-Newton methods in weighted l¹-regularization.
Journal of Inverse and Ill-posed Problems, 21(5):665-693, 2013.
DOI: 10.1515/jip-2013-0031
F. Alexandrov, A. Bartels.
Testing for presence of known and unknown molecules in imaging mass spectrometry.
Bioinformatics, 29(18):2335-2342, 2013.
DOI: 10.1093/bioinformatics/btt388
F. Alexandrov.
The Young PI Buzz: Learning from the Organizers of the Junior Principal Investigator Meeting at ISMB-ECCB 2013.
POLS Computational Biology, 9(11), e10003350 pp., 2013.
DOI: 10.1371/journal.pcbi.1003350
A. Lechleiter, K. Kazimierski, M. Karamehmedovic.
Tikhonov regularization in L^p applied to inverse medium scattering.
Inverse Problems, 29, 075003, IOPscience, 2013.
DOI: doi:10.1088/0266-5611/29/7/075003
online at: Link
M. Lagarrigue, F. Alexandrov, G. Dieuset, A. Perrin, R. Lavigne, S. Baulac, H. Thiele, B. Martin.
A new analysis workflow for MALDI imaging mass spectrometry: application to the discovery and identification of potential markers of Childhood Absence Epilepsy.
Journal of Proteome Research, 11(11):5453-5463, 2012.
DOI: 10.1021/pr3006974
B. Jin, T. Khan, P. Maaß.
A reconstruction algorithm for electrical impedance tomography based on sparsity regularization .
International Journal for Numerical Methods in Engineering, 89(3):337-353, 2012.
DOI: 10.1002/nme.3247
F. Alexandrov, S. Bianconcini, E. B. Dagum, P. Maaß, T. S. McElroy.
A review of some modern approaches to the problem of trend extraction.
Econometric Reviews, 31(6):593-624, Taylor & Francis, 2012.
DOI: 10.1080/07474938.2011.608032
S. Dahlke, U. Friedrich, P. Maaß, T. Raasch, R. Ressel.
An adaptive wavelet solver for a nonlinear parameter identification problem for a parabolic differential equation with sparsity constraints.
Journal of Inverse and Ill-posed Problems, 20(2):213-251, 2012.
DOI: 10.1515/jip-2012-0013
B. Jin, P. Maaß.
An analysis of electrical impedance tomography with applications to Tikhonov regularization.
ESAIM: Control, Optimisation and Calculus of Variations, 18(4):1027-1048, 2012.
DOI: 10.1051/cocv/2011193
A. C. Crecelius, F. Alexandrov, U. S. Schubert.
Application of MALDI-MSI for photolithographic structuring.
Analytical Chemistry, 84(16):6921-6925, 2012.
DOI: 10.1021/ac301616v
D. Trede, S. Schiffler, M. Becker, S. Wirtz, K. Steinhorst, J. Strehlow, M. Aichler, J. H. Kobarg, J. Oetjen, A. Dyatlov, S. Heldmann, A. Walch, H. Thiele, P. Maaß, F. Alexandrov.
Exploring Three-Dimensional Matrix-Assisted Laser Desorption/Ionization Imaging Mass Spectrometry Data: Three-Dimensional Spatial Segmentation of Mouse Kidney.
Analytical Chemistry, 84(14):6079-6087, 2012.
DOI: 10.1021/ac300673y
D. Lorenz, P. Maaß, Q. M. Pham.
Gradient descent for Tikhonov functionals with sparsity constraints: theory and numerical comparison of step size rules.
Electronic Transactions on Numerical Analysis, 39:437-463, 2012.
D. Trede, F. Alexandrov, C. Sagiv, P. Maaß.
Magnification of Label Maps with a Topology-Preserving Level-Set Method.
IEEE Transactions on Image Processing, 21(9):4040-4053 , 2012.
DOI: 10.1109/TIP.2012.2199325
F. Alexandrov.
MALDI imaging mass spectrometry: statistical data analysis and current computational challenges.
BMC Bioinformatics, 13 (Suppl 16): S11; IF2.8 , 2012.
DOI: 10.1186/1471-2105-13-S16-S11
F. Alexandrov, M. Becker, O. Guntinas-Lichius, G. Ernst, F. von Eggeling.
MALDI-imaging segmentation is a powerful tool for spatial functional proteomic analysis of human larynx carcinoma.
Journal of Cancer Research and Clinical Oncology, 139(1):85-95, 2012.
DOI: 10.1007/s00432-012-1303-2
N. Bandeira, J. Watrous, P. Roach, F. Alexandrov, B. S. Heath, J. Y. Yang, R. D. Kersten, M. van der Voort, K. Pogliano, H. Gross, J. M. Raaijmakers, B. S. Moore, J. Laskin, P. C. Dorrestein.
Mass spectral molecular networking of living microbial colonies.
Proceedings of the National Academy of Sciences of the United States of America , 109(26):1743-1752, 2012.
DOI: 10.1073/pnas.1203689109
C. Brandt, P. Maaß, I. Piotrowska-Kurczewski, S. Schiffler, O. Riemer, E. Brinksmeier.
Mathematical methods for optimizing high precision cutting operations.
International Journal of Nanomanufacturing, 8(4):306-325, 2012.
DOI: 10.1504/IJNM.2012.048580
C. M. Rath, F. Alexandrov, S. K. Higginbottom, J. Song, J. L. Sonnenburg, M. E. Milla, M. A. Fischbach, P. C. Dorrestein.
Molecular analysis of model gut microbiotas by imaging mass spectrometry and nano-desorption electrospray ionization reveals dietary metabolite transformations.
Analytical Chemistry, 84(21):9259-9267, 2012.
DOI: 10.1021/ac302039u
M. Ehrhardt, H. Villinger, S. Schiffler.
New Tools for Decomposition of Sea Floor Pressure Data.
Computers & Geosciences, 45:4-12, Elsevier, 2012.
DOI: 10.1016/j.cageo.2012.03.022
online at: http://dx.doi.org/10.1016/j.cageo.2012.03.022
K. Kazimierski, P. Maaß, R. Strehlow.
Norm sensitivity of sparsity regularization with respect to p.
Inverse Problems, 104009 28(10), IOPscience, 2012.
Ausgezeichnet als Highlight Paper

DOI: 10.1088/0266-5611/28/10/104009
D. Trede, J. H. Kobarg, J. Oetjen, H. Thiele, P. Maaß, F. Alexandrov.
On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data.
Journal of Integrative Bioinformatics, 9(1), 189 pp., 2012.
DOI: 10.2390/biecoll-jib-2012-189
online at: JIB open access
B. Jacob, B. Jin, T. Khan, P. Maaß.
Optimal Source for Maximum Distinguishability in Optical Imaging.
Journal of Applied Functional Analysis, 7(4):394-412, 2012.
M. Gehre, T. Kluth, A. Lipponen, B. Jin, A. Seppänen, J. P. Kaipio, P. Maaß.
Sparsity Reconstruction in Electrical Impedance Tomography: An Experimental Evaluation.
Journal of Computational and Applied Mathematics, 236(8):2126-2136, 2012.
DOI: 10.1016/j.cam.2011.09.035
B. Jin, P. Maaß.
Sparsity regularization for parameter identification problems.
Inverse Problems, 123001 28(12), IOPscience, 2012.
Ausgezeichnet als Highlight Paper

DOI: 10.1088/0266-5611/28/12/123001
J. Bruand, F. Alexandrov, S. Sistla, M. Wisztorski, C. Meriaux, M. Becker, M. Salzet, I. Fournier, E. Macagno, V. Bafna.
AMASS: algorithm for MSI (mass spectrometric imaging) analysis by semi-supervised segmentation.
Journal of Proteome Research, 10(10):4734-4743, 2011.
DOI: 10.1021/pr2005378
A. C. Crecelius, F. Alexandrov, U. S. Schubert.
Application of MALDI-MSI to monitor surface changes of UV irradiated poly(styrene) films.
Rapid Communications in Mass Spectrometry, 25(19):2809-14, 2011.
DOI: 10.1002/rcm.5164
D. Lorenz, S. Schiffler, D. Trede.
Beyond convergence rates: exact recovery with the Tikhonov regularization with sparsity constraints.
Inverse Problems, 27(8), 085009(17pp), IOPscience, 2011.
Paper selected in "2011 Highlights for Inverse Problems"

DOI: 10.1088/0266-5611/27/8/085009
online at: arXiv.org e-Print archive
F. Alexandrov, J. H. Kobarg.
Efficient spatial segmentation of large imaging mass spectrometry datasets with spatially aware clustering.
Bioinformatics, 27(13):i230-i238, 2011.
DOI: 10.1093/bioinformatics/btr246
B. Jin, T. Khan, P. Maaß, M. Pidcock.
Function Spaces and Optimal Currents in Impedance Tomography.
Journal of Inverse and Ill-posed Problems, 19(1):25-48, 2011.
DOI: 10.1515/JIIP.2011.022, /May/2011
C. Brandt, J. Niebsch, R. Ramlau, P. Maaß.
Modeling the Influence of Unbalances for Ultra-Precision Cutting Processes.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 91(10):795-808, 2011.
DOI: 10.1002/zamm.201000155
M. Komori, Y. Matsuyama, T. Nirasawa, H. Thiele, M. Becker, F. Alexandrov, T. Saida, M. Tanaka, H. Matsuo, H. Tomimoto, R. Takahashi, K. Tashiro, M. Ikegawa, T. Kondo.
Proteomic pattern analysis discriminates among multiple sclerosis-related disorders.
Annals of Neurology, 71(5):614-623, 2011.
DOI: 10.1002/ana.22633
I. Piotrowska-Kurczewski, J. Vehmeyer.
Simulation Model for Micro-milling Operations and Surface Generation.
, Advanced Materials Research 223:849-858, 2011.
DOI: doi:10.4028/www.scientific.net/AMR.223.849
F. Alexandrov, S. Meding, D. Trede, J. H. Kobarg, B. Balluff, A. Walch, H. Thiele, P. Maaß.
Super-resolution segmentation of imaging mass spectrometry data: Solving the issue of low lateral resolution.
Journal of Proteomics, 75(1):237-245, Elsevier, 2011.
DOI: 10.1016/j.jprot.2011.08.002
J. Watrous, F. Alexandrov, P. C. Dorrestein.
The evolving field of imaging mass spectrometry and its impact on future biological research.
Journal of Mass Spectrometry, 46(2):209-222, 2011.
P. Maaß, N. Sochen.
Uncertainty principles and localization measures.
Operator Algebras and Representation Theory: Frames, Wavelets and Fractals, Oberwolfach Report 17:67-69, 2011.
DOI: 10.4171/OWR/2011/17
P. Maaß.
ZeTeM, Zentrum für Technomathematik, Universität Bremen, Germany.
Newsletter of the European Mathematical Society, March 2011 79:36-38, 2011.
DOI: 10.4171/NEWS
P. Maaß, M. Pidcock, C. Sebu.
A regularized solution for the inverse conductivity problem using mollifiers.
Inverse Problems in Science and Engineering, 18(1):145-161, 2010.
DOI: 10.1080/17415970903234844
T. Hein, K. Kazimierski.
Accelerated Landweber iteration in Banach spaces.
Inverse Problems, 055002 26(5), 2010.
T. Bonesky, S. Dahlke, P. Maaß, T. Raasch.
Adaptive wavelet methods and sparsity reconstruction for inverse heat conduction problems.
Advances in Computational Mathematics, 33(4):385-411, Springer Verlag, 2010.
DOI: 10.1007/s10444-010-9147-2
P. Maaß, C. Sagiv, N. Sochen, H. Stark.
Do Uncertainty Minimizers Attain Minimal Uncertainty?
Journal of Fourier Analysis and Applications, 16(3):448-469, Springer Verlag, 2010.
DOI: 10.1007/s00041-009-9099-4
K. Kazimierski.
Minimization of the Tikhonov functional in Banach spaces smooth and convex of power type by steepest descent in the dual.
Erscheint in Computational Optimization and Applications
F. Alexandrov, M. Becker, S. Deininger, G. Ernst, L. Wehder, M. Grasmair, F. von Eggeling, H. Thiele, P. Maaß.
Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering.
Journal of Proteome Research, 9(12):6535-6546, 2010.
DOI: 10.1021/pr100734z
C. I. Balog, F. Alexandrov, R. J. Derks, P. J. Hensbergen, G. J. van Dam, E. M. Tukahebwa, N. B. Kabatereine, H. Thiele, B. J. Vennervald, O. A. Mayboroda, A. M. Deelder.
The feasibility of mass spectrometry and advanced data processing for monitoring Schistosoma mansoni infection.
Proteomics - Clinical Applications, 4(5):499-510, 2010.
K. Bredies.
A forward-backward splitting algorithm for the minimization of non-smooth convex functionals in Banach space.
Inverse Problems, 25(1), 2009.
DOI: 10.1088/0266-5611/25/1/015005
K. Bredies, D. Lorenz, P. Maaß.
A generalized conditional gradient method and its connection to an iterative shrinkage method.
Computational Optimization and Applications, 42(2):173-193, Springer Verlag, 2009.
DOI: 10.1007/s10589-007-9083-3
F. Alexandrov.
A method of trend extraction using Singular Spectrum Analysis.
RevStat, 7(1):1-22, 2009.
K. Kazimierski.
Are adaptive Mann iterations really adaptive?
Mathematical Communications, 14(2):399 - 412, 2009.
F. Alexandrov, J. Decker, B. Mertens, A. M. Deelder, H. Thiele, P. Maaß, R. A. E. M. Tollenaar.
Biomarker discovery in MALDI-TOF serum protein profiles using discrete wavelet transformation.
Bioinformatics, 25(5):643-649, 2009.
DOI: 10.1093/bioinformatics/btn662
J. Oetjen, B. Reinhold-Hurek.
Characterization of the DraT/DraG System for Posttranslational Regulation of Nitrogenase in the Endophytic Betaproteobacterium Azoarcus sp. Strain BH72.
Journal of Bacteriology, 191(11):3726-3735, 2009.
DOI: 10.1128/JB.01720-08
P. Maaß.
Delay-range-dependent exponential H∞ synchronization of a class of delayed neural networks.
Chaos, Solitons and Fractals, 41(3):1125-1135, Elsevier, 2009.
DOI: 10.1016/j.mcm.2009.05.038
B. Jin, D. Lorenz, S. Schiffler.
Elastic-Net Regularization: Error estimates and Active Set Methods.
Inverse Problems, 25(11), 2009.
DOI: 10.1088/0266-5611/25/11/115022
L. Denis, D. Lorenz, D. Trede.
Greedy Solution of Ill-Posed Problems: Error Bounds and Exact Inversion.
Inverse Problems, 25(11), 115017(24pp), 2009.
DOI: 10.1088/0266-5611/25/11/115017
online at: arXiv.org e-Print archive
L. Denis, D. Lorenz, E. Thiébaut, C. Fournier, D. Trede.
Inline hologram reconstruction with sparsity constraints.
Optics Letters, 34(22):3475-3477, 2009.
DOI: 10.1364/OL.34.003475
online at: HAL (Hyper Articles en Ligne) open archive
T. Bonesky, P. Maaß.
Iterated Soft Shrinkage with Adaptive Operator Evaluations.
Journal of Inverse and Ill-posed Problems, 17(4):337-358, 2009.
DOI: 10.1515/JIIP.2009.023
J. Oetjen, S. Rexroth, B. Reinhold-Hurek.
Mass spectrometric characterization of the covalent modification of the nitrogenase Fe-protein in Azoarcus sp. BH72.
The FEBS Journal, 276(13):3618-3627, 2009.
DOI: 10.1111/j.1742-4658.2009.07081.x
C. Brandt, P. Maaß.
Mathematical model of micro turning process.
The International Journal of Advanced Manufacturing Technology, 45(1):33-40, Springer Verlag, 2009.
DOI: 10.1007/s00170-009-1932-z
M. Lindemann, H. Thiele, P. Maaß, J. Decker.
Support vector classification of proteomic profile spectra based on feature extraction with the bi-orthogonal discrete wavelet transform.
Computing and Visualization in Science, 12(4):189-199, Springer Verlag, 2009.
DOI: 10.1007/s00791-008-0087-z
M. Lukaschewitsch, P. Maaß, M. Pidcock, C. Sebu.
The asymptotic behaviour of weak solutions to the forward problem of electrical impedance tomography on unbounded three-dimensional domains.
Mathematical Methods in the Applied Sciences, 32(2):206-222, WILEY-VCH, 2009.
DOI: 10.1002/mma.1031
P. Maaß.
A convex optimization approach to robust observer-based H∞ control design of linear parameter-varying delayed systems.
International Journal of Modelling, Identification and Control, 4(3):226-241, 2008.
DOI: 10.1504/IJMIC.2008.021160
M. Pidcock, P. Maaß, C. Sebu.
A mollifier method for the inverse conductivity problem.
Journal of Physics, Conference Series, Article ID 012068 135(1), 2008.
DOI: 10.1088/1742-6596/135/1/012068
D. Lorenz, R. Griesse.
A semismooth Newton method for Tikhonov functionals with sparsity constraints.
Inverse Problems, 24(3), 035007, 2008.
DOI: 10.1088/0266-5611/24/3/035007
online at: http://dx.doi.org/10.1088/0266-5611/24/3/035007
K. Kazimierski.
Adaptive Mann iterations for nonlinear accretive and pseudocontractive operator equations.
Mathematical Communications, 13(1):33-44, 2008.
D. D. Haroske.
Atomic decomposition of function spaces with Muckenhoupt weights; an example from fractal geometry.
Mathematische Nachrichten, 281(10), 1476–1494, 2008.
L. Prünte, P. Maaß, H. Thielemann.
Condition Monitoring of linear guideways using a matched wavelet approach.
Signal Processing, 88(7):1656-1670, Elsevier, 2008.
DOI: 10.1016/j.sigpro.2007.12.017
.
Entropy and aproximation numbers of embeddings between weighted besov spaces.
Banach Center Publications, 79:173-185, 2008.
K. Bredies, D. Lorenz.
Iterated hard shrinkage for minimization problems with sparsity constraints.
SIAM Journal on Scientific Computing, 30(2):657-683, 2008.
K. Bredies, D. Lorenz.
Linear Convergence of iterative soft-thresholding.
Journal of Fourier Analysis and Applications, 14(5):813-837, Springer Verlag, 2008.
DOI: 10.1007/s00041-008-9041-1
P. Maaß, B. Kuhfuß, O. Riemer.
Mathematical Models for surface characterization of machining processes.
Microsystem Technologies, 14(12):1989-1993, Springer Verlag, 2008.
DOI: 10.1007/s00542-008-0687-z
I. Loresch, H. Schulte, O. Riemer, P. Maaß, F. Dollinger.
Mathematische Ansätze zur Materialabtragsmodellierung beim Polieren.
HTM - Journal of Heat Treatment and Materials, 63(5):252-256, 2008.
DOI: 10.3139/105.100472
T. Schuster, P. Maaß, T. Bonesky, K. Kazimierski, F. Schöpfer.
Minimization of Tikhonov Functionals in Banach Spaces.
Abstract and Applied Analysis, Article ID 192679, 2008, 18 pages, 2008.
DOI: 10.1155/2008/192679
K. Bredies, D. Lorenz.
On the convergence speed of iterative methods for linear inverse problems with sparsity constraints.
Journal of Physics, Conference Series, 124(1):2031-2043, 2008.
A. Hinrichs, M. Piotrowski.
On the degree of compactness of embeddings between weighted modulation spaces.
, 6(3):303-317, 2008.
D. Lorenz, D. Trede.
Optimal Convergence Rates for Tikhonov Regularization in Besov Scales.
Inverse Problems, 24(5), 055010(14pp), 2008.
DOI: 10.1088/0266-5611/24/5/055010
online at: arXiv.org e-Print archive
C. Brandt, J. Niebsch, R. Ramlau, A. Krause, O. Riemer, P. Maaß.
Process Machine Interaction Model for Turning Processes.
International Journal of Control Theory and Applications, 1(2):145-153, 2008.
F. Alexandrov, N. Golyandina, A. Spirov.
Singular Spectrum Analysis of gene expression profiles of early Drosophila embryo: exponential-in-distance patterns.
Research Letters in Signal Processing, Article ID 825758, 5 pp., 2008.
S. Dahlke, D. Lorenz, P. Maaß, C. Sagiv, G. Teschke.
The Canonical Coherent States Associated With Quotients of the Affine Weyl-Heisenberg Group.
Journal of Applied Functional Analysis, 3(2):215-232, 2008.
S. Dahlke, G. Kutyniok, P. Maaß, C. Sagiv, H. Stark, G. Teschke.
The uncertainty principle associated with the continuous shearlet transform.
International Journal of Wavelets, Multiresolution and Information Processing, 6(2):157-181, 2008.
DOI: 10.1142/S021969130800229X
K. Bredies, T. Bonesky, D. Lorenz, P. Maaß.
A Generalized Conditional Gradient Method for Non-Linear Operator Equations with Sparsity Constraints.
Inverse Problems, 23:2041-2058, 2007.
T. Bonesky, K. Bredies, D. Lorenz, P. Maaß.
A generalized conditional gradient method for nonlinear operator equations with sparsity constraints.
Inverse Problems, 23(5), 2007.
DOI: 10.1088/0266-5611/23/5/014
P. B. Gossiaux, J. Aichelin, C. Brandt, T. Gousset, S. Peigné.
Energy loss of a heavy quark produced in a finite-size quark-gluon plasma.
Journal of Physics G: Nuclear and Particle Physics, 34(8), 2007.
DOI: 10.1088/0954-3899/34/8/S103
P. Maaß, B. Kuhfuß, O. Riemer.
Mathematische Modelle zur tribologischen Optimierung von Zerspanungsprozessen.
Kolloquium Mikroproduktion - Fortschritte, Verfahren, Anwendungen, Kooperation der Sonderforschungsbereiche 440, 499, 516 und 747 :243-248, 2007.
S. D. Moura, M. Piotrowski.
Non-smooth atomic decompositions of anisotropic function spaces and some applications.
Studia Mathematica, 180(2):169-190, 2007.
E. Klann, D. Lorenz, P. Maaß, H. Thiele.
Shrinkage versus Deconvolution.
Inverse Problems, 23:2231-2248, 2007.
DOI: 10.1088/0266-5611/23/5/025
K. Bredies, D. Lorenz, P. Maaß.
An optimal control problem in medical image processing.
Systems, Control, Modeling and Optimization, 202:249-259, Springer Verlag, 2006.
DOI: 10.1007/0-387-33882-9_23
V. Dicken, P. Maaß, R. Ramlau, A. Rienaecker, C. Streller.
Inverse Imbalance Reconstruction in Rotordynamics.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 86(5):385-399, WILEY-VCH, 2006.
DOI: 10.1002/zamm.200410248
E. Klann, P. Maaß, R. Ramlau.
Two-step regularization methods for linear invrse problems.
Journal of Inverse and Ill-posed Problems, 14(6):583-607, 2006.
DOI: 10.1515/156939406778474523
K. Bredies, D. Lorenz, P. Maaß.
Mathematical Concepts of Multiscale Smoothing.
Applied and Computational Harmonic Analysis, 19(2):141-161, Elsevier, 2005.
DOI: 10.1016/j.acha.2005.02.007
V. Dicken, P. Maaß, I. Menz, J. Niebsch, R. Ramlau.
Nonlinear inverse unbalance reconstruction in rotor dynamics.
Inverse Problems in Science and Engineering, 13(5):507-543, 2005.
S. Dahlke, P. Maaß, G. Teschke.
Reconstruction of radar reflectivity densities in a narrowband regime.
IEEE Transactions on Antennas and Propagation, 52(6):1603-1606, 2004.
DOI: 10.1109/TAP.2004.829409
S. Dahlke, P. Maaß.
A Note on Interpolating Scaling functions.
Communications in Applied Analysis, 7(2):265-275, 2003.
S. Dahlke, P. Maaß, G. Teschke.
Interpolating Scaling Functions with Duals.
Journal of Computational Analysis and Application, 5(3):361-373, 2003.
P. Maaß, S. Dahlke, G. Teschke.
Reconstructions of wideband reflectivity densities by wavelets transforms.
Advances in Computational Mathematics, 18(2):189-209, Springer Verlag, 2003.
DOI: 10.1023/A:1021303718373
M. Lukaschewitsch, P. Maaß, M. Pidcock.
Tikhonov regularization for Electrical Impedance Tomography on unbounded domains.
Inverse Problems, 19(3):585-610, 2003.
DOI: 10.1088/0266-5611/19/3/308
T. Köhler, P. Maaß, P. Wust, M. Seebass.
A fast Algorithm to find optimal controls of multiantenna applicators in regional hyperthermia.
Physics in Medicine and Biology, 46:2503-2514, IOPscience, 2001.
DOI: 10.1088/0031-9155/46/9/318
P. Maaß, S. V. Pereverzev, R. Ramlau, S. G. Solodky.
An Adaptive Discretization for Tikhonov-Phillips Regularization with a Posteriori Parameter Selection.
Numerische Mathematik, 87(3):485-502, 2001.
DOI: 10.1007/PL00005421
D. Marpe, G. Blättermann, J. Ricke, P. Maaß.
A Two-Layered Wavelet-Based Algorithm for Efficient Lossless and Lossy Image Compression.
IEEE Transactions on Circuits and Systems for Video Technology, 10(7):1094-1102, 2000.
DOI: 10.1109/76.875514
P. Maaß, G. Teschke, W. Willmann, G. Wollmann.
Detection and Classification of Material Attributes - a practical application of Wavelet Analysis.
IEEE Transactions of Signal Processing, 48(8):2432-2439, 2000.
DOI: 10.1109/78.852022
S. Dahlke, K. Gröchenig, P. Maaß.
A new approach to interpolating scaling functions.
Applicable Analysis - An International Journal, 72(3):485-500, 1999.
DOI: 10.1080/00036819908840755
A. Frommer, P. Maaß.
Fast CG-Based Methods for Tikhonov--Phillips Regularization.
SIAM Journal on Scientific Computing, 20(5):1831-1850, 1999.
DOI: 10.1137/S1064827596313310
K. Dethloff, A. Weisheimer, A. Rinke, D. Handorf, M. V. Kurgansky, W. Jansen, P. Maaß, P. Hupfer.
Climate variability in a nonlinear atmosphere-like dynamical system.
Journal of Geophysical Research, 103:25957-25966, 1998.
DOI: 10.1029/98JD02306
J. Ricke, P. Maaß, E. L. Hänninen, T. Liebig, H. Amthauer, C. Stroszczynski, W. Schauer, T. Boskamp, M. Wolf.
Wavelet Versus JPEG (Joint Photographic Expert Group) and Fractal Compression: Impact on the Detection of Low-Contrast Details in Computed Radiographs.
Investigative Radiology, 33(8):456-463, 1998.
S. Dahlke, P. Maaß.
Interpolating Refinable Functions And Wavelets For General Scaling Matrices.
Numerical Functional Analysis and Optimization, 18(5):521-539, Taylor & Francis, 1997.
DOI: 10.1080/01630569708816776
S. Dahlke, P. Maaß.
A Continuous Wavelet Transform on Tangent Bundles of Spheres.
Journal of Fourier Analysis and Applications, 2(4):379-396, 1996.
P. Maaß, R. Ramlau.
Accelerated iteration methods for inverse problems.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, ICIAM '95 - Sonderband 76:183-186, 1996.
P. Maaß.
Families of Orthogonal 2D Wavelets.
SIAM Journal on Mathematical Analysis, 27(5):1454-1481, 1996.
DOI: 10.1137/S003614109324649X
J. Ewert, P. Maaß.
Local tomography in non-destructive testing.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, ICIAM '95 - Sonderband 76:179-181, 1996.
P. Maaß, R. Ramlau.
Wavelet-accelerated regularization methods for hyperthermia treatment planning.
International Journal of Imaging Systems and Technology, 7(3):191-199, 1996.
V. Dicken, P. Maaß.
Wavelet-Galerkin Methods for Ill-posed Problems.
Journal of Inverse and Ill-posed Problems, 4(3):203-222, 1996.
S. Dahlke, P. Maaß.
Continuous Wavelet Transforms with Applications to Analyzing Functions on Sheres.
Journal of Fourier Analysis and Applications, 2(4):379-396, 1995.
S. Dahlke, P. Maaß.
The Affine Uncertainty Principle in One and Two Dimensions.
Computers & Mathematics with Applications, 30(3):293-305, 1995.
DOI: 10.1016/0898-1221(95)00108-5
P. Maaß, H. Stark.
Wavelets and digital image processing.
Surveys on Mathematics for Industry, 4(3):195-235, 1994.
P. Maaß.
The Interior Radon Transform.
SIAM Journal on Applied Mathematics, 52(3):710-724, 1992.
DOI: 10.1137/0152040
P. Maaß, W. Treimer, U. Feye-Treimer.
Tomographic Methods for 2D Reconstructions with the Double Cristal Diffractometer.
IMPACT of Computing in Science and Engineering, 4(3):250-268, Elsevier, 1992.
DOI: 10.1016/0899-8248(92)90003-Q
W. Treimer, P. Maaß, B. Strothmann, U. Feye-Treimer.
High-resolution neutron small-angle scattering with a double-crystal diffractometer and 2D reconstruction.
Physica B: Condensed Matter, 174(1):532-536, Elsevier, 1991.
DOI: 10.1016/0921-4526(91)90652-U
A. K. Louis, P. Maaß.
Smoothed projection methods for the moment problem .
Numerische Mathematik, 59(1):277-294, Springer Verlag, 1991.
DOI: 10.1007/BF01385781
A. K. Louis, P. Maaß.
A mollifier method for linear operator equations of the first kind.
Inverse Problems, 6(3):427-440, IOPscience, 1990.
DOI: 10.1088/0266-5611/6/3/011
P. Maaß.
Tomographische Methoden bei Breitband Radar.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 70(6):539-540, 1990.
P. Maaß.
Wideband radar: the hyp transform .
Inverse Problems, 5(5):849-857, IOPscience, 1989.
DOI: 10.1088/0266-5611/5/5/012
P. Maaß.
3D Röntgentomographie: Ein Auswahlkriterium für Abtastkurven.
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 68:498-499, 1988.
E. Hairer, P. Maaß.
Numerical methods for singular nonlinear integro-differential equations .
Applied Numerical Mathematics, 3(3):243-246, Elsevier, 1987.
DOI: 10.1016/0168-9274(87)90051-1
P. Maaß.
The x-ray transform: singular value decomposition and resolution.
Inverse Problems, 3(4):729-741, IOPscience, 1987.
DOI: 10.1088/0266-5611/3/4/016
.
.
, .
A. C. Crecelius, F. Alexandrov, U. S. Schubert.
Application of MALDI-MSI to monitor surface changes of UV irradiated poly(styrene) films.
Research Letters in Signal Processing, 25(19):2809-14.

Proceedings (76)

M. Nittscher, M. F. Lameter, R. Barbano, J. Leuschner, B. Jin, P. Maaß.
SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstruction.
Medical Imaging with Deep Learning (MIDL 2023), 10.07.-12.07.2023.

online at: https://2023.midl.io/papers/p014
M. Nitzsche, H. Albers, T. Kluth, B. Hahn.
Compensating model imperfections during image reconstruction via resesop.
International Workshop on Magnetic Particle Imaging, 21.03.-23.03.2022, Würzburg, Germany.
International Journal on Magnetic Particle Imaging, 8(1):4 pages, 2022.
DOI: 10.18416/IJMPI.2022.2203062
H. Albers, T. Kluth.
Immobilized nanoparticles with uniaxial anisotropy in multi-dimensional lissajous-type excitation: An equilibrium model approach.
International Workshop on Magnetic Particle Imaging, 21.03.-23.03.2022, Würzburg, Germany.
International Journal on Magnetic Particle Imaging, 8(1):4 pages, 2022.
DOI: 10.18416/IJMPI.2022.2203048
M. Beckmann, A. Bhandari.
MR. TOMP: Inversion of the Modulo Radon Transform (MRT) via Orthogonal Matching Pursuit (OMP).
2022 IEEE International Conference on Image Processing (ICIP), 16.10.-19.10.2022.
M. Schmidt.
Around the clock - capsule networks and image transformations.
PAMM.
Proceedings in Applied Mathematics and Mechanics, 20(1):e202000179, 2021.
DOI: 10.1002/pamm.202000179
online at: https://onlinelibrary.wiley.com/doi/abs/10.1002/pamm.202000179
M. Schmidt, A. Denker, J. Leuschner.
The Deep Capsule Prior - advantages through complexity.
GAMM 91st Annual Meeting of the international Association of Applied Mathematics and Mechanics, online, 15.03.2021 - 19.03.2021.
Proceedings in Applied Mathematics & Mechanics, 21(1), WILEY-VCH, 2021.
DOI: 10.1002/pamm.202100166
S. Dittmer, T. Kluth, D. Otero Baguer, B. Maass.
A Deep Prior Approach to Magnetic Particle Imaging.
Machine Learning for Medical Image Reconstruction 2020.
Springer International Publishing, F. Deeba, P. Johnson, T. Würfl, J. C. Ye (Eds.), pp. 113-122, 2020.
DOI: 10.1007/978-3-030-61598-7_11
A. Denker, M. Schmidt, J. Leuschner, P. Maaß, J. Behrmann.
Conditional Normalizing Flows for Low-Dose Computed Tomography Image Reconstruction.
ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models, 18.07-18.07.2020, Vienna, Austria.

online at: https://invertibleworkshop.github.io/accepted_papers/index.html
M. Möddel, F. Griese, T. Kluth, T. Knopp.
Estimating orientation using multi-contrast MPI.
10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Eds.), 6(2):3 pages, Infinite Science Publishing, 2020.
DOI: 10.18416/IJMPI.2020.2009023
F. Tramer, J. Behrmann, N. Carlini, N. Papernot, J. Jacobsen.
Fundamental Tradeoffs between Invariance and Sensitivity to Adversarial Perturbations.
International Conference on Machine Learning (ICML), 12.07 - 18.07.2020, Vienna, Austria.

online at: https://arxiv.org/abs/2002.04599
H. Albers, T. Kluth, T. Knopp.
MNPDynamics: A computational toolbox for simulating magnetic moment behavior of ensembles of nanoparticles.
10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Eds.), 6(2):3 pages, Infinite Science Publishing, 2020.
DOI: 10.18416/IJMPI.2020.2009020
T. Kluth, P. Szwargulski, T. Knopp.
Towards accurate modeling of the multidimensional MPI physics.
10th International Workshop on Magnetic Particle Imaging 2020, Würzburg, 07.09.-09.09.2020.
International Journal on Magnetic Particle Imaging, T. Knopp, T. M. Buzug (Eds.), 6(2):2 pages, Infinite Science Publishing, 2020.
DOI: 10.18416/IJMPI.2020.2009004
J. Behrmann, P. Vicol, K. Wang, R. Grosse, J. Jacobsen.
On the Invertibility of Invertible Neural Networks.
NeurIPS workshop on Machine Learning with Guarantees, 2019.

online at: https://sites.google.com/view/mlwithguarantees/accepted-papers
T. Czotscher, D. Otero Baguer, F. Vollertsen, I. Piotrowska-Kurczewski, P. Maaß.
Connection Between Shock Wave Induced Indentations And Hardness By Means Of Neural Networks.
22nd International Conference on Material Forming (ESAFORM 2019), 08.05.-10.05.2019.
AIP Conference Proceedings 2113, 100001, Springer Verlag, 2019.
DOI: 10.1063/1.5112634
J. Jacobsen, J. Behrmann, R. Zemel, M. Bethge.
Excessive Invariance Causes Adversarial Vulnerability.
International Conference on Learning Representations (ICLR), 2019.

online at: https://openreview.net/forum?id=BkfbpsAcF7
J. Jacobsen, J. Behrmann, N. Carlini, F. Tramer, N. Papernot.
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness.
SafeML Workshop, ICLR, 2019.

online at: https://arxiv.org/abs/1903.10484
J. Behrmann, W. Grathwohl, R. T. Chen, D. Duvenaud, J. Jacobsen.
Invertible Residual Networks.
International Conference on Machine Learning (ICML).
Proceedings of Machine Learning Research, 97:573-582, 2019.
Long Oral

online at: http://proceedings.mlr.press/v97/behrmann19a.html
C. Etmann, S. Lunz, P. Maaß, C. Schönlieb.
On the Connection Between Adversarial Robustness and Saliency Map Interpretability.
36th International Conference on Machine Learning, 09.06.-15.06.2019, Los Angeles, USA.
PMLR 97, 97:1823-1832, 2019.
online at: http://proceedings.mlr.press/v97/etmann19a.html
R. T. Chen, J. Behrmann, D. Duvenaud, J. Jacobsen.
Residual Flows for Invertible Generative Modeling.
Advances in Neural Information Processing Systems (NeurIPS).
32, pp. 9916--9926, 2019.
Spotlight

online at: https://papers.nips.cc/paper/9183-residual-flows-for-invertible-generative-modeling
T. Kluth, B. Hahn, C. Brandt.
Spatio-temporal concentration reconstruction using motion priors in magnetic particle imaging.
International Workshop on Magnetic Particle Imaging 2019.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2019, pp. 23-24, Infinite Science Publishing, 2019.
T. Kluth, B. Jin.
Exploiting Ill-Posedness in Magnetic Particle Imaging - System Matrix Approximation via Randomized SVD.
International Workshop on Magnetic Particle Imaging 2018.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2018, pp. 127-128, Infinite Science Publishing, 2018.
J. Flötotto, T. Kluth, M. Möddel, T. Knopp, P. Maaß.
Improving Generalization Properties of Measured System Matrices by Using Regularized Total Least Squares Reconstruction in MPI.
International Workshop on Magnetic Particle Imaging 2018.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2018, pp. 53-54, Infinite Science Publishing, 2018.
D. Otero Baguer, P. Maaß.
Inverse Problems in designing new structural materials.
7th International Conference on High Performance Scientific Computing, 19.03-23.03.2018, Hanoi, Vietnam.

DOI: 10.1007/978-3-030-55240-4_8
P. Gralla, D. . Rippel, M. Lütjen, P. Maaß.
Inverting Prediction Models in Micro Production for Process Design.
5TH INTERNATIONAL CONFERENCE ON NEW FORMING TECHNOLOGY, 18.09.-21.09.2018, Bremen, Germany.

DOI: 10.1051/matecconf/201819015007
C. Bathke, T. Kluth, P. Maaß.
MPI Reconstruction Using Structural Prior Information and Sparsity.
International Workshop on Magnetic Particle Imaging 2018.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2018, pp. 129-130, Infinite Science Publishing, 2018.
K. Tracht, A. Onken, P. Gralla, J. H. Emad, N. Kipry, P. Maaß.
Trend-specific clustering for micro mass production of linked parts.
CIRP General Assembly 2018, 19.08-25.08.2018.
CIRP Annals, Manufacturing Technology, 67(1):9-12, Elsevier, 2018.
DOI: 10.1016/j.cirp.2018.04.017
C. Bathke, T. Kluth, C. Brandt, P. Maaß.
Improved image reconstruction in magnetic particle imaging using structural a priori information.
International Workshop on Magnetic Particle Imaging 2017.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2017, pp. 85, Infinite Science Publishing, 2017.
T. Kluth, P. Maaß.
Model uncertainty in magnetic particle iamging: Motivating nonlinear problems by model-based sparse reconstruction.
International Workshop on Magnetic Particle Imaging 2017.
International Workshop on Magnetic Particle Imaging (IWMPI) Book of Abstracts 2017, pp. 83, Infinite Science Publishing, 2017.
A. Schmidt, C. Niebuhr, D. Niederwestberg, J. Vehmeyer.
Modelling, simulation, and optimization of thermal deformations from milling processes.
ECMI 2016.
Mathematics in Industry, 26:337-343, Springer Verlag, 2017.
A. Schmidt, E. Bänsch, M. Jahn, A. Luttmann, C. Niebuhr, J. Vehmeyer.
Optimization of Engineering Processes Including Heating in Time-Dependent Domains.
27th IFIP TC 7 Conference, CSMO 2015, 29.06.-03.07.2015.
IFIP AICT Series , 494:452-461, Springer Verlag, 2017.
P. Gralla, I. Piotrowska-Kurczewski, P. Maaß.
Tikhonov Functionals Incorporating Tolerances.
88th GAMM Annual Meeting of the international Association of Applied Mathematics and Mechanics (GAMM).
To appear in Proc. Appl. Math. Mech..
P. Gralla, I. Piotrowska-Kurczewski, P. Maaß.
Parameter identification for micro milling processes using inverse problems incorporating tolerances.
International Congress on engineering, design and Manufacturing 2016, 08.09-10.09.2016, Barcelona, Spain.
T. Boskamp, D. Lachmund, J. Oetjen, Y. Hernandez-Cordero, J. Behrmann, J. H. Kobarg, R. Casadonte, J. Kriegsmann, P. Maaß.
Visualizing MALDI TOF datasets of FFPE tissue samples for the purpose of quality assessment and comparison.
OurCon IV - 2016, 17.10.-21.10.2016, Ustron, Poland.

online at: http://www.bioradint.eu/ourcon_public/papersview.php?showdetail=&paper_id=45
T. Reineking, T. Kluth, D. Nakath.
Adaptive information selection in images: Efficient naive bayes nearest neighbor classification.
16th International Conference on Computer Analysis of Images and Patterns, Valetta, Malta, 2016, London, UK.
Lecture Notes in Computer Science, Proceedings CAIP, 9256:350-361, 2015.
DOI: 10.1007/978-3-319-23192-1_29
W. Zhang, G. Luo, L. Shen, T. Page, P. Li, M. Jiang, P. Maaß, J. Cong.
FPGA acceleration by asynchronous parallelization for simultaneous image reconstruction and segmentation based on the Mumford-Shah regularization.
SPIE OPTICAL ENGINEERING + APPLICATIONS, 09.08.-13.08.2015, San Diego, USA.
Image Reconstruction from Incomplete Data VIII, Volume 9600, P. J. Bones, M. A. Fiddy, R. P. Millane (Eds.), SPIE, 2015.
DOI: 10.1117/12.2187898
J. Vehmeyer, I. Piotrowska-Kurczewski, F. Böhmermann, O. Riemer, P. Maaß.
Least-squares based parameter identification for a function-related surface optimisation in micro ball-end milling.
15th CIRP Conference on Modelling Machining Operations (CIRP CMMO), 11.07.-12.07.2015, Karlsruhe, Germany.
Procedia CIRP, 31:276-281, Elsevier, 2015.
DOI: 10.1016/j.procir.2015.03.076
B. Denkena, A. Schmidt, P. Maaß, D. Niederwestberg, C. Niebuhr, J. Vehmeyer.
Prediction of Temperature Induced Shape Deviations in dry Milling.
15th CIRP Conference on Modelling Machining Operations (CIRP CMMO), 11.07.-12.07.2015, Karlsruhe, Germany.
Procedia CIRP, 31:340-345, Elsevier, 2015.
DOI: 10.1016/j.procir.2015.03.072
online at: http://www.sciencedirect.com/science/article/pii/S221282711500387X
P. Li, T. Page, G. Luo, W. Zhang, P. Zhang, P. Wang, P. Maaß, M. Jiang, J. Cong.
FPGA Acceleration for Simultaneous Medical Image Reconstruction and Segmentation .
2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines , 11.05.-13.05.2014, Boston, MA, USA.

DOI: 10.1109/FCCM.2014.54
J. Vehmeyer, I. Piotrowska-Kurczewski, S. Twardy.
A surface generation model for micro cutting processes with geometrically defined cutting edges.
MATADOR 37th International Conference, 25th – 27th July, 2012.
2013, XVII, 448 p. 582 illus, Proceedings of the 37th International MATADOR Conference, pp. 149-152, 2013.
A. Bartels, D. Trede, F. Alexandrov, P. Maaß.
Hybrid Regularization and Sparse Reconstruction of Imaging Mass Spectrometry Data.
10th International Conference on Sampling Theory and Applications (SampTA'13), 01.07.-05.07.2013, Bremen, Germany.

online at: http://www.eurasip.org/Proceedings/Ext/SampTA2013/papers/p189-bartels.pdf
I. Chernyavsky, F. Alexandrov, P. Maaß.
A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data.
German Conference on Bioinformatics 2012.

DOI: 10.4230/OASIcs.GCB.2012.39
D. Trede.
Exact support recovery for linear inverse problems with sparsity constraint.
International Conference on Inverse Problems , 26.04.-29,04.2010, Wuhan, China.
Methods and Applications of Analysis, 18(1):105-110, International Press, Boston, Massachusetts, USA, 2011.
online at: http://www.intlpress.com/MAA/MAA-v18.php#MAA-18-1
D. Trede, J. H. Kobarg, K. Steinhorst, F. Alexandrov.
Mathematical Methods for Imaging Mass Spectrometry.
14th Joint International IMEKO TC1+TC7+TC13 Symposium, 31.08.-02.09.2011, Jena, Germany.
Best Paper Award at IMEKO Symposium Jena

online at: URN: urn:nbn:de:gbv:ilm1-2011imeko-082:8
C. Brandt, J. Niebsch, J. Vehmeyer.
Modelling of Ultra-precision Turning Process in Consideration of Unbalances.
13th CIRP Conference on Modeling of Machining Operations, 12-05.-13.05.2011, Sintra, Portugal.
Proceedings of the 13th CIRP Conference on Modeling of Machining Operations, 223:839-848, 2011.
DOI: 10.4028/www.scientific.net/AMR.223.839
J. Niebsch, R. Ramlau, C. Brandt.
On the interaction of unbalances and surface quality in ultra-precision cutting machinery.
9. Internationale Tagung Schwingungen in rotierenden Systemen SIRM 2011, 21.-23. Februar 2011, Darmstadt, Germany.
Proceedings of the 9th International Conference SIRM 2011, Vibrations in rotating machines, 2011.
E. Ovchinnikova, S. Borgo, A. Oltramari, L. Vieu, F. Alexandrov.
Data-driven and ontological analysis of FrameNet for natural language reasoning.
7th Int. Conf. on Language Resources and Evaluation (LREC'10), 2010.
F. Alexandrov, O. Keszöcze, S. Schiffler, K. Steinhorst.
Peak detection in mass spectrometry data using sparse coding.
COMPSTAT'10.
C. Brandt, J. Niebsch, P. Maaß, R. Ramlau.
Simulation of Process Machine Interaction for Ultra Precision Turning.
2nd International Conference on Process Machine Interactions, 10.06.-11.06.2010, Vancouver, Canada.
Proceedings of the 2nd International Conference on Process Machine Interactions, 2010.
F. Alexandrov, O. Keszöcze, S. Schiffler, K. Steinhorst, D. Lorenz.
An active set approach to the elastic-net and its applications in mass spectrometry.
Second Workshop "Signal Processing with Adaptive Sparse Structured Representations" (SPARS′09), 06.04.-09.04.2009, St. Malo, France.

online at: http://hal.inria.fr/inria-00369397/en/
E. Ovchinnikova, F. Alexandrov, T. Wandmacher.
Automatic acquisition of the argument-predicate relations from a frame-annotated corpus.
Conference on Empirical Methods in Natural Language Processing (EMNLP’09), 2009.
C. Brandt, A. Krause, E. Brinksmeier, P. Maaß.
Force modelling in diamond machining with regard to the surface generation process.
9th International Conference and Exhibition on Laser Metrology, machine tool, CMM and robotic performance, 30.06.-02.07.2009, London, UK.
Proceedings of the 9th International Conference and Exhibition on Laser Metrology, machine tool, CMM and robotic performance, LAMDAMAP 2009, pp. 377-386, 2009.
D. Lorenz, D. Trede.
Greedy Deconvolution of Point-like Objects.
Second Workshop "Signal Processing with Adaptive Sparse Structured Representations" (SPARS′09), 06.04.-09.04.2009, St. Malo, France.
A. Pehlken, A. Decker, P. Maaß, D. H. Müller, K. D. Thoben, S. Todt, M. Rolbiecki, W. Wosniok.
Knowledge Based Recycling Concept.
SETAC Europe 19th Annual Meeting, 31.05.2009 - 04.06.2009, Gothenburg, Sweden.
A. Pehlken, A. Decker, P. Maaß, D. H. Müller, M. Rolbiecki, K. D. Thoben, S. Todt.
LC thinking in combination with meta-modeling technique applied to recycling processes.
4th International Conference on Life Cycle Management, 06.09.2009 - 09.09.2009, Cape Town, South Africa.
D. Lorenz, D. Trede.
Optimal Convergence Rates for Tikhonov Regularization in Besov Scales.
4th International Conference on Inverse Problems: Modeling and Simulation, 26.05.-30.05.2008, Fethiye, Turkey.
Journal of Inverse and Ill-Posed Problems, 17(1):69-76, 2009.
DOI: 10.1515/JIIP.2009.008
F. Alexandrov.
Self-taught learning for classification of mass spectrometry data: a case study of colorectal cancer.
German Conference on Bioinformatics'09.
Lecture Notes in Informatics 157, pp. 45-54, 2009.
F. Alexandrov.
A method of trend extraction using Singular Spectrum Analysis.
International Conference on Computational Statistics, 24.08-29.08.2008, Porto, Portugal.
To appear in Proceedings of COMPSTAT'08.
K. Bredies.
An iterative thresholding-like algorithm for inverse problems with sparsity constraints in Banach space.
4th International Conference on Inverse Problems: Modeling and Simulation, 26.05.-30.05.2008, Fethiye, Turkey.
To appear in Journal of Inverse and Ill-Posed Problems.
F. Alexandrov, N. Golyandina, A. Timofeyev.
Dependence of accuracy of ESPRIT estimates on signal eigenvalues: the case of a noisy sum of two real exponentials.
79th Annual Meeting of the International Association of Applied Mathematics and Mechanics, 31.03-04.04.2008, Bremen, Germany.
Proceedings in Applied Mathematics and Mechanics, 8(1):10761–10762, 2008.
DOI: 10.1002/pamm.200810761
T. Wandmacher, E. Ovchinnikova, F. Alexandrov.
Does latent semantic analysis reflect human associations?
20th European Summer School in Logic, Language and Information, 04.08.-15.08.2008, Hamburg, Germany.
Proceedings of the 20th European Summer School in Logic, Language and Information, M. Baroni, S. Evart, A. Lenci (Eds.), pp. 63-70, 2008.
I. Loresch, H. Schulte, O. Riemer, E. Brinksmeier, P. Maaß, F. Dollinger.
Mathematical Approaches for the Modelling of Material Removal in Polishing Processes.
The 1st International Conference on NanoManufacturing, 13.07.-16.07.2008, Singapur, .
To appear in Proceedings of the 1st International Conference on NanoManufacturing.
C. Brandt, P. Maaß.
Model development for turning process.
6th International Conference on Manufacturing Research, 09.09.-11.09.2008, Brunel University, West London, UK.
Proceedings of the 6th International Conference on Manufacturing Research, pp. 859-866, 2008.
C. Brandt, J. Niebsch, R. Ramlau, A. Krause, O. Riemer, P. Maaß.
Process-Machine Interaction Model for Turning Process.
The 1st International Conference on Process Machine Interactions, 03.09-04.09.2008, Leibniz Universität Hannover, Germany.
Proceedings of the 1st International Conference on Process Machine Interactions, pp. 239-246, 2008.
K. Bredies, F. Alexandrov, J. Decker, D. Lorenz, H. Thiele.
Sparse deconvolution for peak picking and ion charge estimation in mass spectrometry.
15th European Conference on Mathematics in Industry'08, 30.06.-04.07.2008, London, UK.
To appear in Proceedings of 15th European Conference on Mathematics in Industry'08.
D. Lorenz, P. Maaß, H. Preckel, D. Trede.
Topology-preserving geodesic active contours for segmentation of high-content fluorescent cellular imaging.
79th Annual Meeting of the International Association of Applied Mathematics and Mechanics, 31.03-04.04.2008, Bremen, Germany.
Proceedings in Applied Mathematics and Mechanics, 8(1):10941-10942, 2008.
DOI: 10.1002/pamm.200810941
A. Decker, P. Maaß, D. H. Müller, A. Pehlken, M. Rolbiecki, K. D. Thoben, S. Todt, W. Wosniok.
Unsicherheitsanalyse des Aufbereitungsprozesses am Beispiel Altreifenrecycling.
Aufbereitung und Recycling 2008, 12.11.-13.11.2008, Freiberg, Germany.
To appear in Tagungskompendium Aufbereitung und Recycling 2008.
G. Teschke, U. Görsdorf, P. Körner, D. Trede.
A New Approach for Target Classification of Ka-Band Radar Data.
Fourth European Conference on Radar in Meteorology and Hydrology (ERAD), 18.09-22.09.2006, Barcelona, Spain.
K. Bredies, D. Lorenz, P. Maaß.
An optimal control problem in image processing.
PAMM.
Proceedings in Applied Mathematics and Mechanics, 6(1):859-860, 2006.
DOI: 10.1002/pamm200610409
T. Bonesky, K. Bredies, D. Lorenz, P. Maaß.
On the minimization of non-convex, non-differentiable functionals with an application to SPECT.
Oberwolfach Report: Mathematical Methods in Tomography.
R. Nordmann, D. Peters, B. Domes, P. Maaß.
Inverse Determination of Imbalance Distributions.
8th International Conference on Vibrations in Rotating Machinery, 07.09.-09.09.2004, Swansea, .
S. Dahlke, P. Maaß.
An outline of adaptive wavelet galerkin methods for tikhonov regularization of inverse parabolic problems.
International Conference on Inverse Problems, 09.01.-12.01.2002, , China.
Recent development in Theories and Numerics, Y. Hon, M. Yamamoto, J. Cheng, J. Lee (Eds.), pp. 56-66, World Scientific, 2002.
DOI: 10.1142/9789812704924_0006
M. Quante, G. Teschke, M. Zhariy, P. Maaß, K. Sassen.
Extraction and analysis of structural features in cloud radar and lidar data using wavelet based methods.
2nd European conference on Radar Meteorology, ERAD, 18.11.-22.11.2002, , Netherlands.
ERAD Publication Series, H. Russchenberg (Eds.), 1:95-103, Copernicus Verlag, 2002.
V. Dicken, P. Maaß, B. Ott, M. Thierschmann.
Eignung von Wavelet-Bilddatenkompressionsverfahren für Satellitenbildaufnahmen.
Deutscher Luft- u. Raumfahrtkongress - DGLR Jahrestagung 1995, 26.09.-29.09.1995.
P. Maaß.
Singular value decompositions for Radon transforms.
Oberwolfach Report: Mathematical Methods in Tomography.

DOI: 10.1007/BFb0084504
P. Fernsel, Z. Kereta, A. Denker.
Convergence Properties of Score-Based Models using Graduated Optimisation for Linear Inverse Problems.
IEEE International Workshop on Machine Learning for Signal Processing (2024), 22.09.-25.09.2024, London, UK.
To appear in IEEE.
online at: https://arxiv.org/abs/2404.18699
P. Gralla, I. Piotrowska-Kurczewski, D. . Rippel, M. Lütjen, P. Maaß.
Eine Methode zur Invertierung von Vorhersagemodellen in der Mikrofertigung.
8. Kolloquium Mikroproduktion, 27.11.-28.11.2017, Bremen, Germany.

Book Chapters (33)

P. Maaß, L. Hauberg-Lotte, T. Boskamp.
MALDI Imaging: Exploring the Molecular Landscape.
German Success Stories in Industrial Mathematics, H. Bock, K. Küfer, P. Maaß, A. Milde, V. Schulz (Eds.), Mathematics in Industry, pp. 97-103, Springer Verlag, 2022.
DOI: 10.1007/978-3-030-81455-7_17
P. Maaß, S. Dittmer, T. Kluth, J. Leuschner, M. Schmidt.
Mathematische Architekturen für Neuronale Netze.
Erfolgsformeln – Anwendungen der Mathematik, M. Ehrhardt, M. Günther, W. Schilders (Eds.), Mathematische Semesterberichte, pp. 190-195, Springer Verlag, 2022.
DOI: 10.1007/s00591-022-00325-y
J. Behrmann, M. Schmidt, J. Wildner, P. Maaß, S. Schmale.
Purity Assessment of Pellets Using Deep Learning.
German Success Stories in Industrial Mathematics, H. Bock, K. Küfer, P. Maaß, A. Milde, V. Schulz (Eds.), Mathematics in Industry, pp. 29-34, Springer Verlag, 2022.
DOI: 10.1007/978-3-030-81455-7_6
P. Maaß.
Deep learning for trivial inverse problems.
Compressed Sensing and its Applications, H. Boche, R. Calderbank, G. Caire, G. Kutyniok, R. Mathar, P. Petersen (Eds.), Applied and Numerical Harmonic Analysis, pp. 195-209, Birkhäuser, 2019.
DOI: 10.1007/978-3-319-73074-5_6
O. Riemer, P. Maaß, F. E. Elsner-Dörge, P. Gralla, J. Vehmeyer, M. Willert, A. Meier, I. Zahn.
Predictive compensation measures for the prevention of shape deviations of mircomilled dental products.
Cold Micro Metal Forming, Springer Verlag, 2018.
B. Denkena, P. Maaß, A. Schmidt, D. Niederwestberg, J. Vehmeyer, C. Niebuhr, P. Gralla.
Thermomechanical Deformation of Complex Workpieces in Milling and Drilling Processes.
Thermal Effects in Complex Machining Processes - Final Report of the DFG Priority Program 1480, D. Biermann, F. Hollmann (Eds.), LNPE, pp. 219-250, Springer Verlag, 2017.
E. Ovchinnikova, N. Montazeri, F. Alexandrov, J. Hobbs, M. C. McCord, R. Mulkar-Mehta .
Abductive Reasoning with a Large Knowledge Base for Discourse Processing.
Computing Meaning, 47, pp. 107-127, Springer Verlag, 2013.
DOI: 10.1007/978-94-007-7284-7_7
M. Andres, H. Blum, C. Brandt, C. Carstensen, P. Maaß, J. Niebsch, A. Rademacher, R. Ramlau, A. Schröder, E. Stephan, S. Wiedemann.
Adaptive finite Elements and Mathematical Optimization Methods.
Process Machine Interactions, B. Denkena, F. Hollmann (Eds.), Lecture Notes in Production Engineering, pp. 53-77, Springer Verlag, 2013.
DOI: 10.1007/978-3-642-32448-2
J. H. Kobarg, F. Alexandrov.
Efficient spatial segmentation of hyper-spectral 3D volume data.
Algorithms from and for Nature and Life, B. Lausen, D. Van den Poel, A. Ultsch (Eds.), Studies in Classification, Data Analysis, and Knowledge Organization, pp. 95-103, Springer Verlag, 2013.
DOI: 10.1007/978-3-319-00035-0_9
I. Piotrowska-Kurczewski, C. Brandt, P. Maaß, O. Riemer.
Inverse Modelling.
Micro Metal Forming, F. Vollertsen (Eds.), ISBN: 978-3-642-30915-1, pp. 267-288, Springer Verlag, 2013.
C. Brandt, A. Krause, J. Niebsch, J. Vehmeyer, E. Brinksmeier, P. Maaß, R. Ramlau.
Surface Generation Process with Consideration of the Balancing State in Diamond Machining.
Process Machine Interactions, B. Denkena, F. Hollmann (Eds.), Lecture Notes in Production Engineering, pp. 329-360, Springer Verlag, 2013.
DOI: 10.1007/978-3-642-32448-2
G. J. Bauer, D. Lorenz, P. Maaß, H. Preckel, D. Trede.
Compounds, Drugs and Mathematical Image Processing.
Production Factor Mathematics, M. Grötschel, K. Lucas, V. Mehrmann (Eds.), pp. 379-392, Springer Verlag, 2010.
DOI: 10.1007/978-3-642-11248-5_20
P. Maaß, O. Riemer.
Flexible Herstellung von tribologisch optimierten Mikroumformwerkzeugen.
4. Kolloquium Mikroproduktion, F. Vollertsen (Eds.), pp. 281-286, BIAS Verlag, 2009.
S. Dahlke, P. Maaß, G. Teschke, K. Koch, D. Lorenz, S. Müller, S. Schiffler, A. Stämpfli, H. Thiele, M. Werner.
Multiscale Approximation.
Mathematical Methods in Time Series Analysis and Digital Image Processing, R. Dahlhaus, J. Kurths, P. Maaß, J. Timmer (Eds.), pp. 75-109, Springer Verlag, 2008.
G. J. Bauer, D. Lorenz, P. Maaß, H. Preckel, D. Trede.
Wirkstoffe, Medikamente und mathematische Bildverarbeitung.
Produktionsfaktor Mathematik - wie Mathematik Technik und Wirtschaft bewegt, M. Grötschel, K. Lucas, V. Mehrmann (Eds.), acatech DISKUTIERT, pp. 461-477, acatech - Deutsche Akademie der Technikwissenschaften, 2008.
DOI: 10.1007/978-3-540-89435-3_20
M. Kulesh, B. Berkels, K. Bredies, C. S. Garbe, J. F. Acker, M. S. Diallo, M. Droske, M. Holschneider, J. Hron, C. Kondermann, P. Maaß, N. Olischläger, H. Peitgen, T. Preusser, M. Rumpf, F. Scherbaum, S. Turek.
Inverse Problems and Parameter Identification in Image Processing.
Mathematical Methods in Signal Processing and Digital Image Analysis, R. Dahlhaus, J. Kurths, P. Maaß, J. Timmer (Eds.), pp. 111-151, Springer Verlag, 2007.
DOI: 10.1007/978-3-540-75632-3
K. Bredies, D. Lorenz, P. Maaß, G. Teschke.
A partial differential equation for continuous non-linear shrinkage filtering and its application for analyzing MMG data.
Wavelet Applications in Industrial Processing, F. Truchetet (Eds.), 5266, pp. 84-93, SPIE, 2004.
DOI: 10.1117/12.515945
S. Dahlke, P. Maaß.
An outline of adaptive wavelet galerkin methods for Tikhonov regularization of inverse parabolic problems.
Recent Development in Theories and Numerics, Y. Hon, M. Yamamoto, J. Cheng, J. Lee (Eds.), pp. pp. 56-66, World Scientific, 2003.
DOI: 10.1142/9789812704924_0006
P. Maaß, C. Boeckmann, A. Mekler.
Improvement of environment observing remote sensing devices by regularization techniques.
Mathematics - key technology for the futore, W. Jäger, H. Krebs (Eds.), pp. 162-172, Springer Verlag, 2003.
V. Dicken, I. Menz, J. Niebsch, P. Maaß, R. Ramlau.
Inverse Unwuchtidentifikation an Flugtriebwerken mit Quetschöldämpfern.
Schwingungen in rotierenden Machinen VI, Sirm 2003, A. Irretier, R. Nordmann, H. Springer (Eds.), pp. 123-137, Vieweg Verlag, 2003.
P. Maaß, M. Ende, D. Kayser, W. Osten, G. Teschke.
Continuous wavelet methods in signal processing.
Fringe 2001: 4th International Workshop on Automatic Processing of Fringe Patterns, W. Osten, W. Jüptner (Eds.), pp. 142-153, Elsevier, 2001.
T. Köhler, P. Maaß, M. Seebass, P. Wust.
Efficient methods for Hyperthermia treatment planning.
Surveys on Solution Methods for Inverse Problems, D. Colton, H. W. Engl, A. K. Louis, J. R. Laughlin, W. Rundell (Eds.), pp. 155-168, Springer Verlag, 2000.
P. Maaß.
Wavelet Methods and Applications in Physics.
Advanced Mathematical Methods in Metrology IV, P. Ciarlini, M. G. Cox, F. Pavese, D. Richter (Eds.), World Scientific, 1998.
P. Maaß, T. Boskamp, V. Dicken, R. Bischoff, H. Peters, H. Stark.
Bilddatenkompression mit Wavelet-Methoden.
Mathematik: Schlüsseltechnologie für die Zukunft, Verbundprojekte zwischen Universität und Industrie, F. Hoffmann, W. Jäger, B. Lohmann, H. Schunck (Eds.), pp. 385-394, Springer Verlag, 1997.
P. Maaß.
Wavelet Methods in Signal Processing.
Advanced Mathimatical Tools in Metrology III, P. Ciarlini, M. G. Cox, F. Pavese, D. Richter (Eds.), pp. 91-104, World Scientific, 1997.
P. Maaß, A. Rieder.
Wavelet-accelerated Tikholov-regularisation with applications.
Inverse Peoblems in Medical Imaging and Nondestructive Testing, H. W. Engl, A. K. Louis, W. Rundell (Eds.), pp. 134-159, Springer Verlag, 1997.
M. Ende, A. K. Louis, P. Maaß, G. Mayer-Kress.
EEG signal analysis by continuous wavelet transform techniques.
Nonlinear Analysis of Physiological Data, H. Kantz, G. Mayer-Kress, J. Kurths (Eds.), pp. 213-219, Springer Verlag, 1996.
P. Maaß.
Wavelet-projection methods for inverse problems.
Beiträge zur Angewandten Analysis und Numerik, E. Schock (Eds.), pp. 231-224, Shaker Verlag, 1994.
H. Hammer, P. Maaß, A. Rieder, J. Meyer.
Wavelet Analysis of Auscultatory Blood Pressure Signals.
Abstracts of the second European conference on Engineering and Medicine, pp. 322-323, Elsevier, 1993.
P. Maaß.
Wideband approximation and Wavelet Transform.
Radar and Sonar, Part II, F. A. Grünbaum, M. Bernfeld, R. E. Blahut (Eds.), pp. 83-88, Springer Verlag, 1992.
P. Maaß.
Singular value decompositions for Radon transforms.
Mathematical Aspects of Computerized Tomography, G. T. Herman, A. K. Louis, F. Natterer (Eds.), Lecture Notes in Mathematics, pp. 6-14, Springer Verlag, 1991.
DOI: 10.1007/BFb0084504
P. Maaß.
A generalized radon transform in wideband radar.
Integral Geometry and Tomography, E. Grinberg, E. T. . Quinto (Eds.), AMs - Contemporary Mathematics, pp. 183-188, AMS - American Mathematical Society, 1990.
P. Maaß.
Generalized Backus-Gilbert Methods.
Inverse Methods in Action, P. Sabatier (Eds.), pp. 440-446, Springer Verlag, 1990.

PhD/Habilitation Thesis (36)

D. . Dobrovolskij.
3D image analysis and microstructure models for simulation of materials properties.
Dissertationsschrift, Universität Bremen, 2024.
DOI: 10.26092/elib/3052
A. Denker.
Invertible Neural Networks and Normalizing Flows for Image Reconstruction.
Dissertationsschrift, Universität Bremen, 2024.
DOI: 10.26092/elib/2921
L. Kinzel.
Unsupervised Deep Machine Learning Methods to Discriminate Icequakes in Seismological Data from Neumayer Station, Antarctica.
Dissertationsschrift, Universität Bremen, 2024.
DOI: 10.26092/elib/3013
J. Leuschner.
Deep Learning for Computed Tomography Reconstruction: Learned Methods, Deep Image Prior, and Uncertaninty Estimation.
Dissertationsschrift, Universität Bremen, 2023.
DOI: 10.26092/elib/2704
D. Nganyu Tanyu.
On the Interplay between Deep Learning Partial Differential Equations and Inverse Problems.
Dissertationsschrift, Universität Bremen, 2023.
P. Gralla.
Tikhonov Functionals Incorporating Tolerances in Discrepancy Term for Inverse Problems.
Dissertationsschrift, Universität Bremen, 2023.
DOI: 10.26092/elib/2097
M. Schmidt.
Hybrid Deep Learning: How Combining Data-Driven and Model-Based Approaches Solves Inverse Problems in Computed Tomography and Beyond.
Dissertationsschrift, Universität Bremen, 2022.
DOI: 10.26092/elib/1941
P. Fernsel.
Nonnegative Matrix Factorization: Theory, Algorithms and Applications.
Dissertationsschrift, Universität Bremen, 2022.
DOI: 10.26092/elib/1493
online at: https://doi.org/10.26092/elib/1493
G. Sfakianaki.
Regularization of ill-posed inverse problems with tolerances and sparsity in parameter space.
Dissertationsschrift, Universität Bremen, 2021.
DOI: 10.26092/elib/1065
online at: https://media.suub.uni-bremen.de/bitstream/elib/5269/1/Georgia_Sfakianaki_PhD_Dissertation_2021_final_pdfA.pdf
C. Etmann.
Double Backpropagation with Applications to Robustness and Saliency Map Interpretability.
Dissertationsschrift, Universität Bremen, 2020.
D. Otero Baguer.
Neural Networks for solving Inverse Problems. Applications in Materials Science and Medical Imaging. (submitted).
Dissertationsschrift, Universität Bremen, 2020.
S. Dittmer.
On deep learning applied to inverse problems - A chicken-and-egg problem.
Dissertationsschrift, Universität Bremen, 2020.
C. Brandt.
Recurrence Quantification Compared to Fourier Analysis for Ultrasonic Non-Destructive Testing of Fibre Reinforced Polymers.
Dissertationsschrift, Universität Bremen, 2020.
J. Behrmann.
Principles of Neural Network Architecture Design: Invertibility and Domain Knowledge.
Dissertationsschrift, Universität Bremen, 2019.
online at: https://elib.suub.uni-bremen.de/peid/D00108536.html
D. Lantzberg.
Quantum Frames and Uncertainty Principles arising from Symplectomorphisms.
Dissertationsschrift, Universität Bremen, 2019.
online at: http://nbn-resolving.de/urn:nbn:de:gbv:46-00107143-11
T. H. Nguyen.
Mathematical aspects of catalyst positioning in Lithium-air batteries.
Dissertationsschrift, Universität Bremen, 2018.
online at: Elektronische Bibliothek der Universität Bremen
J. Vehmeyer.
Geometrische Modellierung und funktionsbezogene Optimierung der inhärenten Textur von Mikrofräsprozessen.
Dissertationsschrift, Universität Bremen, Logos Verlag, 2016.
P. Dülk.
Aspects of parameter identification in semilinear reaction-diffusion systems .
Dissertationsschrift, Universität Bremen, 2015.
online at: Elektronische Bibliothek der Universität Bremen
T. Page.
Image reconstruction by Mumford-Shah regularization with a priori edge information.
Dissertationsschrift, Universität Bremen, 2015.
Ausgezeichnet mit dem Studienpreis der unifreunde Bremen

online at: Elektronische Bibliothek der Universität Bremen
A. Bartels.
Data Compression and Compressed Sensing in Imaging Mass Spectrometry and Sporadic Communication.
Dissertationsschrift, Universität Bremen, Logos Verlag, 2014.
online at: http://www.logos-verlag.de/cgi-bin/buch/isbn/3850
R. Strehlow.
Regularization of the inverse medium problem : on nonstandard methods for sparse reconstruction.
Dissertationsschrift, Universität Bremen, 2014.
online at: http://elib.suub.uni-bremen.de/edocs/00104187-1.pdf
J. H. Kobarg.
Signal and image processing methods for imaging mass spectrometry data.
Dissertationsschrift, Universität Bremen, 2014.
online at: http://nbn-resolving.de/urn:nbn:de:gbv:46-00104098-10
B. Kanning.
Instationary Vibrational Analysis for Impulse-type Stimulated Structures.
Dissertationsschrift, Universität Bremen, Logos Verlag, 2013.
C. Brandt.
Regularization of Inverse Problems for Turning Processes.
Dissertationsschrift, Universität Bremen, Logos Verlag, 2013.
online at: http://logos-verlag.de/cgi-bin/buch?isbn=3323
Q. M. Pham.
Sparsity constraints and regularization for nonlinear inverse problems .
Dissertationsschrift, Universität Bremen, 2012.
online at: Elektronische Bibliothek der Universität Bremen
K. Chen.
Optimal Control Based Image Sequence Interpolation.
Dissertationsschrift, Universität Bremen, 2011.
online at: Elektronische Bibliothek der Universität Bremen
K. Kazimierski.
Aspects of regularization in Banach spaces.
Dissertationsschrift, Universität Bremen, 2010.
D. Trede.
Inverse problems with sparsity constraints: Convergence rates and exact recovery.
Dissertationsschrift, Universität Bremen, Logos Verlag, 2010.
M. Zhariy.
Adaptive Frame Based Regularization Methods For Linear Ill-Posed Inverse Problems.
Dissertationsschrift, Universität Bremen, 2009.
T. Bonesky.
Regularization of inverse problems and inexact operator evaluations.
Dissertationsschrift, Universität Bremen, 2009.
L. Prünte.
Learning Wavelet-Dictionaries and Continuous Dictionaries.
Dissertationsschrift, Universität Bremen, 2008.
K. Bredies.
Optimal control of degenerate parabolic equations in image processing.
Dissertationsschrift, Universität Bremen, 2007.
Ausgezeichnet mit dem Studienpreis der unifreunde Bremen
D. Trede.
Parameteroptimierung und Segmentieren mit aktiven Konturen für die High-Content-Analyse beim Hochdurchsatz-Screening.
Diplomarbeit, Universität Bremen, unpublished diploma thesis, 2007.
.
Weighted Function Spaces and Traces on Fractals.
Dissertationsschrift, Friedrich-Schiller-Universität Jena, 2006.
P. Maaß.
Die Konstruktion orthogonaler Wavelets und Anwendungen.
Habilitationsschrift, Universität des Saarlandes, 1993.
P. Maaß.
Die Singulärwertzerlegung der Röntgen-Transformation und ihre Anwendungen in der Computer-Tomographie.
Dissertationsschrift, Technische Universität Berlin, 1988.

Preprints (48)

J. G. Maaß, R. Herdt, L. Kinzel, M. Walther, H. Fröhlich, T. Schubert, C. Schaaf, P. Maaß.
Enhancing the analysis of murine neonatal ultrasonic vocalizations: Development, evaluation, and application of different mathematical models.
Zur Veröffentlichung eingereicht.
C. Arndt, S. Dittmer, N. Heilenkötter, M. Iske, T. Kluth, J. Nickel.
Bayesian view on the training of invertible residual networks for solving linear inverse problems.
Zur Veröffentlichung eingereicht.
online at: https://www.x-mol.net/paper/article/1682514725633245184
C. Brandt, T. Kluth, T. Knopp, L. Westen.
Dynamic image reconstruction with motion priors in application to 3d magnetic particle imaging.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2306.11625
D. Nganyu Tanyu, J. Ning, A. Hauptmann, B. Jin, P. Maaß.
Electrical Impedance Tomography: A Fair Comparative Study on Deep Learning and Analytic-based Approaches.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2310.18636
M. Beckmann, N. Heilenkötter.
Equivariant Neural Networks for Indirect Measurements.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2306.16506
M. Beckmann, A. Bhandari, M. Iske.
Fourier-Domain Inversion for the Modulo Radon Transform.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2307.13114
R. Barbano, J. Antorán, J. Leuschner, J. M. Hernández-Lobato, B. Jin, Z. Kereta.
Image Reconstruction via Deep Image Prior Subspaces.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2302.10279
T. Lütjen, F. Schönfeld, J. Leuschner, M. Schmidt, A. Wald, T. Kluth.
Learning-based approaches for reconstructions with inexact operators in nanoCTapplications.
Zur Veröffentlichung eingereicht.
online at: https://aps.arxiv.org/abs/2307.10474
R. Herdt, M. Schmidt, D. Otero Baguer, J. Le Clerc Arrastia, P. Maaß.
Model Stitching and Visualization How GAN Generators can Invert Networks in Real-Time.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2302.02181
S. Dittmer, M. Roberts, J. Preller, .. AIX-COVNET Collaboration, J. H. F. Rudd, J. A. D. Aston, C. Schönlieb.
Reinterpreting survival analysis in the universal approximator age.
Zur Veröffentlichung eingereicht.
M. Roberts, A. Hazan, S. Dittmer, J. H. F. Rudd, C. Schönlieb.
The curious case of the test set AUROC.
Zur Veröffentlichung eingereicht.
H. Albers, T. Kluth.
Time-dependent parameter identification in a Fokker-Planck equation based magnetization model of large ensembles of nanoparticles.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2307.03560
R. Barbano, J. Leuschner, J. Antorán, B. Jin, J. M. Hernández-Lobato.
Bayesian Experimental Design for Computed Tomography with the Linearised Deep Image Prior.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2207.05714
S. Dittmer, D. Erzmann, H. Harms, P. Maaß.
SELTO: Sample-Efficient Learned Topology Optimization.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2209.05098
T. Grossmann, S. Dittmer, Y. Korolev, C. Schönlieb.
Unsupervised Learning of the Total Variation Flow.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2206.04406#
P. Fernsel, P. Maaß.
Regularized Orthogonal Nonnegative Matrix Factorization and K-means Clustering.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2112.07641
L. Kuger, G. Rigaud.
Joint fan-beam CT and Compton scattering tomography: analysis and image reconstruction.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2008.06699
S. . Mukherjee, S. Dittmer, Z. . Shumaylov, S. Lunz, O. Öktem, C. Schönlieb.
Learned convex regularizers for inverse problems.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2008.02839
I. Piotrowska-Kurczewski, G. Sfakianaki.
Tikhonov functionals with a tolerance measure introduced in the regularization.
Zur Veröffentlichung eingereicht.
online at: http://arxiv.org/abs/2007.06431
J. Behrmann, P. Vicol, K. Wang, R. Grosse, J. Jacobsen.
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/2006.09347
G. Rigaud.
3D Compton scattering imaging: study of the spectrum and contour reconstruction.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1908.03066
C. Etmann.
A Closer Look at Double Backpropagation.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1906.06637
S. Dittmer, P. Maaß.
A Projectional Ansatz to Reconstruction.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1907.04675
C. Etmann, M. Schmidt, J. Behrmann, T. Boskamp, L. Hauberg-Lotte, A. Peter, R. Casadonte, J. Kriegsmann, P. Maaß.
Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1912.05459
T. Kluth, B. Jin.
Exploiting heuristic parameter choice rules for one-click image reconstruction in magnetic particle imaging.
Zur Veröffentlichung eingereicht.
R. . Grotheer, T. . Strauss, P. Gralla, T. Khan.
Alternatives for Generating a Reduced Basis to Solve the Hyperspectral Diffuse Optical Tomography Model.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1803.00948
J. Behrmann, S. Dittmer, P. Fernsel, P. Maaß.
Analysis of Invariance and Robustness via Invertibility of ReLU-Networks.
Zur Veröffentlichung eingereicht.
online at: https://arxiv.org/abs/1806.09730
K. Chen, D. Lorenz.
Image Sequence Interpolation based on Optical Flow, Segmentation, and Optimal Control.
Berichte aus der Technomathematik 11-11, Universität Bremen, 2011.
K. Chen, D. Lorenz.
Image sequence interpolation using optimal control.
Berichte aus der Technomathematik 11-01, Universität Bremen, 2011.
M. Ehrhardt, H. Villinger, S. Schiffler.
New Tools for Decomposition of Sea Floor Pressure Data.
Berichte aus der Technomathematik 11-03, Universität Bremen, 2011.
P. Maaß, Q. M. Pham.
Semismooth Newton and Quasi-Newton Methods in Weighted l¹-Regularization of Nonlinear Inverse Problems.
Berichte aus der Technomathematik 11-02, Universität Bremen, 2011.
P. Maaß, Q. M. Pham.
Sparsity regularization of the diffusion coefficient problem: well-posedness and convergence rates.
Berichte aus der Technomathematik 11-04, Universität Bremen, 2011.
L. C. Martin, G. Teschke.
A new method to reconstruct radar reflectivities and Doppler information.
Berichte aus der Technomathematik 04-01, Universität Bremen, 2004.
J. Soares, G. Teschke, M. Zhariy.
A Wavelet Regularization for Nonlinear Diffusion Equations.
Berichte aus der Technomathematik 04-12, Universität Bremen, 2004.
R. Ramlau.
On the use of fixed point iterations for the regularization of nonlinear ill-posed problems.
Berichte aus der Technomathematik 04-06, Universität Bremen, 2004.
I. Daubechies, G. Teschke.
Variational image restoration by means of wavelets: simultaneous decomposition, deblurring and denoising.
Berichte aus der Technomathematik 04-04, Universität Bremen, 2004.
I. Daubechies, G. Teschke.
Wavelet based image decomposition by variational functionals.
Berichte aus der Technomathematik 04-02, Universität Bremen, 2004.
V. Dicken, P. Maaß, I. Menz, J. Niebsch, R. Ramlau.
Nonlinear Inverse Unbalance Reconstruction in Rotor dynamics.
Berichte aus der Technomathematik 03-08, Universität Bremen, 2003.
G. Teschke.
Construction of Generalized Uncertainty Principles and Wavelets in Anisotropic Sobolev Spaces.
Berichte aus der Technomathematik 02-06, Universität Bremen, 2002.
R. Ramlau.
TIGRA - an iterative algorithm for regularizing nonlinear ill-posed problems.
Berichte aus der Technomathematik 02-07, Universität Bremen, 2002.
T. Köhler, P. Maaß.
Time-series forecasting for total volume data and charge back data.
Berichte aus der Technomathematik 02-10, Universität Bremen, 2002.
S. Dahlke, G. Steidl, G. Teschke.
Coorbit Spaces and Banach Frames on Homogeneous Spaces with Applications to Analyzing Functions on Spheres.
Berichte aus der Technomathematik 01-13, Universität Bremen, 2001.
R. Ramlau.
Morozov's Discrepancy Principle for Tikhonov regularization of nonlinear operators.
Berichte aus der Technomathematik 01-08, Universität Bremen, 2001.
S. Dahlke, P. Maaß, G. Teschke.
Reconstruction of Reflectivity Desities by Wavelet Transforms.
Berichte aus der Technomathematik 01-10, Universität Bremen, 2001.
R. Ramlau.
A steepest descent algorithm for the global minimization of Tikhonov-Phillips functional.
Berichte aus der Technomathematik 00-19, Universität Bremen, 2000.
F. Stenger, A. R. Naghsh-Nilchi, J. Niebsch, R. Ramlau.
A unified approach to the approximate solution of PDE.
Berichte aus der Technomathematik 00-17, Universität Bremen, 2000.
R. Ramlau, R. Clackdoyle, F. Noo, G. Bal.
Accurate Attenuation Correction in SPECT Imaging using Optimization of Bilinear Functions and Assuming an Unknown Spatially-Varying Attenuation Distribution.
Berichte aus der Technomathematik 00-14, Universität Bremen, 2000.
V. Lehmann, G. Teschke.
Wavelet Based Methods for Improved Wind Profiler Signal Processing.
Berichte aus der Technomathematik 00-12, Universität Bremen, 2000.

Miscellaneous (14)

C. Brandt, M. Hamann, J. Leuschner.
Regression Models for Ultrasonic Testing of Carbon Fiber Reinforced Polymers.
Berichte aus der Technomathematik 19–01, Universität Bremen, 2019.
P. Gralla.
Inverse Problems Using Reduced Basis Method.
All Theses, 2014.
Master Thesis

online at: http://tigerprints.clemson.edu/all_theses/2007
T. Hein, K. Kazimierski.
Modified Landweber iteration in Banach spaces - convergence and convergence rates.
TU Chemnitz, Fakultät für Mathematik, Preprint 14, 2009.
K. Steinhorst, O. Keszöcze, F. Alexandrov.
Mass spectrometry and wavelet approximation.
Projektbericht, Universität Bremen, 2008.
C. Evers, K. Hachmann, M. Linden, A. Luttmann, K. Bredies, P. Maaß, F. Alexandrov.
The Technomatika toolbox: LCMS peakpicking and alignment.
Projektbericht, Universität Bremen, 2008.
L. Justen, P. Maaß.
Verbesserte dynamische Festzieleliminierung beim Niederschlagsradar.
Projektbericht, Universität Bremen, 2008.
S. Dahlke, P. Maaß.
An Outline of Adaptive Wavelet Galerkin Methods for Tikhonov Regularization of Inverse Parabolic Problems.
Berichte aus der Technomathematik 02-02, Universität Bremen, 2002.
V. Dicken, P. Maaß, I. Menz, J. Niebsch, R. Ramlau.
Inverse Unwuchtidentifikation an Flugtriebwerken mit Quetschöldämpfern.
Berichte aus der Technomathematik 02-09, Universität Bremen, 2002.
P. Maaß, T. Köhler, J. Kalden, L. R. Costa, U. Parlitz, C. Merkwirth, U. Wichard.
Mathematical methods for forecasting bank transaction data.
Projektbericht, Preprint Series DFG-SPP 1114, Preprint 24, 2002.
M. Lukaschewitsch, P. Maaß, M. Pidcock.
Tikhonov regularization for Electrical Impedance Tomography on unbounded domains.
Berichte aus der Technomathematik 02-08, Universität Bremen, 2002.
T. Köhler, P. Maaß, P. Wust, M. Seebass.
Efficient methods in hyperthermia treatment planning.
Berichte aus der Technomathematik 01-01, Universität Bremen, 2001.
S. Dahlke, P. Maaß.
A Note on Interpolating Scaling Functions.
Berichte aus der Technomathematik 00-13, Universität Bremen, 2000.
P. Maaß, G. Teschke, W. Willmann, G. Wollmann.
Detection and Classification of Material Attributes -- A Practical Applicaion of Wavelet Analysis.
Berichte aus der Technomathematik 00-10, Universität Bremen, 2000.
S. Dahlke, P. Maaß, G. Teschke.
Interpolating Scaling Functions with Duals.
Berichte aus der Technomathematik 00-08, Universität Bremen, 2000.

Center for Industrial Mathematics

ZeTeM > Working Groups > WG Industrial Mathematics > Publications

Publications of WG Industrial Mathematics

Monographies (4)

Articles (220)

Proceedings (76)

Book Chapters (33)

PhD/Habilitation Thesis (36)

Preprints (48)

Miscellaneous (14)