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Zeitschriftenartikel (527)

  1. 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

  2. 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 unter: https://www.sciencedirect.com/science/article/abs/pii/S0304885321007678

  3. 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

  4. F. Alexandrov.
    A method of trend extraction using Singular Spectrum Analysis.
    RevStat, 7(1):1-22, 2009.
  5. 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

  6. 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

  7. 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 S., 2013.

    DOI: 10.1371/journal.pcbi.1003350

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. F. Alexandrov, P. E. . Bourne.
    Learning how to run a lab: interviews with Principal Investigators.
    POLS Computational Biology, 9(11), e1003349 S., 2013.

    DOI: 10.1371/journal.pcbi.1003349

  14. 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

  15. 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 S., 2008.
  16. 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

  17. 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

  18. 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

  19. I. Altrogge, T. Preusser, T. Kröger, C. Büskens, P. L. Pereira, D. Schmidt, H. Peitgen.
    Multiscale Optimization of the Probe Placement for Radiofrequency Ablation.
    Academic Radiology, 14(11):1310-1324 , 2007.
  20. 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 unter: https://doi.org/10.1038/s41467-019-12880" target="doi">015 | https://doi.org/10.1038/s41467-019-12880

  21. T. Arens, D. Gintides, A. Lechleiter.
    Direct and inverse medium scattering in a 3D homogeneous planar waveguide.
    SIAM Journal on Applied Mathematics, 71:753-772, SIAM, 2011.

    DOI: 10.1137/100806333
    online unter: http://dx.doi.org/10.1137/100806333

  22. T. Arens, D. Gintides, A. Lechleiter.
    Variational formulations for scattering in a 3-dimensional acoustic waveguide.
    Mathematical Methods in the Applied Sciences, 31:821-847, WILEY-VCH, 2008.

    DOI: 10.1002/mma.947
    online unter: http://onlinelibrary.wiley.com/doi/10.1002/mma.947/abstract

  23. T. Arens, A. Lechleiter.
    Indicator Functions for Shape Reconstruction Related to the Linear Sampling Method.
    SIAM Journal on Imaging Sciences, 8(1):513-535, SIAM, 2015.

    DOI: 10.1137/140965740

  24. T. Arens, A. Lechleiter, D. R. . Luke .
    MUSIC for extended scatterers as an instance of the Factorization method.
    SIAM Journal on Applied Mathematics, 70:1283-1304, SIAM, 2009.

    DOI: 10.1137/080737836
    online unter: http://dx.doi.org/10.1137/080737836

  25. T. Arens, A. Lechleiter.
    The linear sampling method revisited.
    Journal of Integral Equations and Applications, 21:179-202, 2009.

    DOI: 10.1216/JIE-2009-21-2-179
    online unter: http://projecteuclid.org/euclid.jiea/1242652032

  26. T. Arens, K. Sandfort, S. Schmitt, A. Lechleiter.
    Analysing Ewald's method for the evaluation of Green's functions for periodic media.
    IMA Journal of Applied Mathematics, 78(3):405-431, 2013.

    DOI: 10.1093/imamat/hxr057
    online unter: Link

  27. 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

  28. 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

  29. J. Aurich, D. Biermann, H. Blum, A. Kirsch, A. Rademacher, A. Scheidler.
    Vergleich unterschiedlicher Prozesssimulationen für das Flachschleifen und ihre Kopplung mit einer Finite-Elemente-Maschinensimulation.
    Schleifen und Polieren, 4:44-50, 2011.
  30. E. Bänsch, A. Luttmann, J. Montalvo Urquizo, A. Schmidt, M. G. Villarreal-Marroquin.
    Simulation and multi-objective optimization to improve the final shape and process efficiency of a laser-based material accumulation process.
    Journal of Mathematics in Industry, 10(2), 30 p., 2020.
  31. E. Bänsch, J. Paul, A. Schmidt.
    An ALE finite element method for a coupled Stefan problem and Navier-Stokes equations with free capillary surface.
    International Journal for Numerical Methods in Fluids, Article first published online : 6 AUG 2012, DOI: 10.1002/fld.3711 , Wiley, 2012.

    DOI: 10.1002/fld.3711

  32. 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.
  33. 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

  34. 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

  35. 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

  36. 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

  37. M. Beckmann, P. Maaß, J. Nickel.
    Error analysis for filtered back projection reconstructions in Besov spaces.
    Inverse Problems, 37 014002 37(1), IOPscience, 2020.
  38. 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

  39. J. Benedetto, E. King.
    Smooth functions associated with wavelet sets on ℝd, d≥1, and frame bound gaps.
    Acta Applicandae Mathematicae, 107(1):121-142, 2009.

    DOI: 10.1007/s10440-008-9412-2

  40. F. Beyer, H. Blum, D. Kumor, A. Rademacher, K. Willner, T. Schneider.
    Experimental and simulative investigations of tribology in sheet-bulk metal forming.
    Key Engineering Materials, 639:283-290, 2015.
  41. D. Biermann, H. Blum, I. Iovkov, N. Klein, A. Rademacher, F. Suttmeier.
    Stabilization techniques and a posteriori error estimates for the obstacle problem.
    Applied Mathematical Sciences, 7(127):6329-6346, 2013.
  42. D. Biermann, I. Iovkov, H. Blum, A. Rademacher, K. Taebi, F. Suttmeier, N. Klein.
    Wendeltiefbohren mit Minimalmengenschmierung - Experimentelle Analyse und FE-Simulation der thermischen Werkstückbelastung.
    VDI-Z Integrierte Produktion, 154(4):62-65, 2012.
  43. H. Blum, H. Frohne, J. Frohne, A. Rademacher.
    Semi-smooth Newton methods for mixed FEM discretizations of higher-order for frictional, elasto-plastic two-body contact problems.
    , 309:131-151, 2016.
  44. H. Blum, T. Jansen, A. Rademacher, K. Weinert.
    Finite elements in space and time for dynamic contact problems.
    International Journal on Numerical Methods in Engineering, 76:1632-1644, 2008.
  45. H. Blum, A. Rademacher, A. Schröder.
    Goal oriented error control for frictional contact problems in metal forming.
    Key Engineering Materials, 504:987-992, 2012.
  46. H. Blum, A. Rademacher, A. Schröder.
    Space adaptive finite element methods for dynamic obstacle problems.
    Electronic Transactions on Numerical Analysis, 32:162-172, 2008.
  47. H. Blum, A. Rademacher, A. Schröder.
    Space adaptive finite element methods for dynamic Signorini problems.
    Computational Mechanics, 44(4):481-491, 2009.
  48. H. Blum, K. Weinert, T. Jansen, T. Mohn, A. Rademacher.
    Angepasste Simulationstechnik zur Analyse NC-gesteuerter Formschleifprozesse.
    Zeitschrift für wirtschaftlichen Fabrikbetrieb, 101(6):422-425, 2006.
  49. P. Bobrov, J. Montalvo Urquizo, A. Schmidt, W. Wosniok.
    Mechanic-Stochastic Model for the Simulation of Polycrystals.
    PAMM, Vol. 10(1):279-280, WILEY-VCH, 2010.

    DOI: 10.1002/pamm.201010132

  50. 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

  51. M. Böhm, J. Devinny, F. Jahani, I. G. Rosen.
    On a moving-boundary system modeling corrosion in sewer pipes.
    Applied Mathematics and Computation, 92:247-269, Elsevier, 1998.
  52. M. Böhm, M. Höpker.
    A note on modelling with measures: Two-Features Balance Equations.
    Mathematical Biosciences and Engineering, 12(2):279-290, 2015.

    DOI: 10.3934/mbe.2015.12.279

  53. M. Böhm, M. Hunkel, A. Schmidt, M. Wolff.
    Evaluation of various phase-transition models for 100Cr6 for application in commercial FEM-programmes.
    Journal de Physique, 4(120):581-589, 2004.
  54. M. Böhm, S. Meier, M. Peter.
    Was zerstört Stahlbeton-Brücken? - Wie Mathematiker mit Mehrskalenmethoden zur Materialforschung beitragen.
    Praxis der Mathematik in der Schule, 20:39-43, 2008.
  55. S. Bökenheide, M. Wolff.
    Comparison of different approaches to verify creep behaviour of 100Cr6 steel.
    Computational Materials Science, 64:34-37, Elsevier, 2012.

    DOI: 10.1016/j.commatsci.2012.04.016
    online unter: http://dx.doi.org/10.1016/j.commatsci.2012.04.016

  56. S. Bökenheide, M. Wolff, M. Dalgic, D. Lammers, T. Linke.
    Creep, phase transformations and transformation-induced plasticity of 100Cr6 steel during heating.
    Materialwissenschaft und Werkstofftechnik, 43(1):143-149, WILEY-VCH, 2012.

    DOI: 10.1002/mawe.201100902

  57. C. Böß, A. S. Lawless, N. Nichols, A. Bunse-Gerstner.
    State estimation using model order reduction for unstable systems.
    Computers & Fluids, 46(1):155-160, Elsevier, 2011.

    DOI: 10.1016/j.compfluid.2010.11.033

  58. S. Boettcher.
    Existence and uniqueness of the solution of thermo-elasto-plasticity with phase transitions in TRIP steels under mixed boundary conditions.
    Journal of Applied Analysis, 24(1):87-98, 2018.

    DOI: 10.1515/jaa-2018-0009

  59. S. Boettcher, M. Böhm, M. Wolff.
    Well-posedness of a thermo-elasto-plastic problem with phase transitions in TRIP steels under mixed boundary conditions.
    ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 95:1461-1476, 2015.

    DOI: 10.1002/zamm.201300287

  60. 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

  61. 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

  62. 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

  63. 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 unter: https://doi.org/10.1021/acs.analchem.1c01792

  64. 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

  65. 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 unter: https://doi.org/10.1021/acs.analchem.9b04473

  66. S. Bosse, A. Lechleiter.
    A hybrid approach for structural monitoring with self-organizing multi-agent systems and inverse numerical methods in material-embedded sensor networks.
    Mechatronics, 34:12-37, 2016.

    DOI: 10.1016/j.mechatronics.2015.08.005
    online unter: Link

  67. I. Bougoudis, A. Blechschmidt, A. Richter, S. Seo, J. P. Burrows, N. Theys, A. Rinke.
    Long-term Time-series of Arctic Tropospheric BrO derived from UV-VIS Satellite Remote Sensing and its Relation to First Year Sea Ice.
    Erscheint in Atmospheric Chemistry and Physics

    DOI: 10.5194/acp-2020-116

  68. I. Bougoudis, K. Demertzis, L. Iliadis, V. . Anezakis, A. Papaleonidas.
    FuSSFFra, a fuzzy semi-supervised forecasting framework: the case of the air pollution in Athens.
    Neural Computing and Applications, 7, 2018.
  69. H. Brachtendorf, A. Bunse-Gerstner, B. Lang, S. Lampe, A. Awasthi.
    Quasiperiodic steady-state analysis of electronic circuits by a spline basis.
    Mathematics in Industry, 14(2):199-206, Springer Verlag, 2010.

    DOI: 10.1007/978-3-642-12294-1_26

  70. H. Brachtendorf, A. Bunse-Gerstner, B. Lang, S. Lampe.
    Steady state analysis of electronic circuits by cubic and exponential spline.
    Electrical Engineering (Archiv für Elektrotechnik), 91(4):287-299, Springer Verlag, 2009.

    DOI: 10.1007/s00202-009-0137-7
    online unter: http://www.springerlink.com/content/604x1247152u3576/

  71. 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.
  72. 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

  73. 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

  74. 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

  75. 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.
  76. 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

  77. 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

  78. K. Bredies, D. Lorenz.
    Iterated hard shrinkage for minimization problems with sparsity constraints.
    SIAM Journal on Scientific Computing, 30(2):657-683, 2008.
  79. 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

  80. 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

  81. 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.
  82. 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

  83. C. Buchheim, R. Kuhlmann, C. Meyer.
    Combinatorial Optimal Control of Semilinear Elliptic PDEs.
    Computational Optimization and Applications, 70(3):641-675, 2018.

    COAP 2018 Best Paper Award

    DOI: 10.1007/s10589-018-9993-2

  84. F. Bürgel, K. Kazimierski, A. Lechleiter.
    A sparsity regularization and total variation based computational framework for the inverse medium problem in scattering.
    Journal of Computational Physics, 339, 1–30, 2017.

    DOI: 10.1016/j.jcp.2017.03.011

  85. F. Bürgel, K. Kazimierski, A. Lechleiter.
    IPscatt—A MATLAB Toolbox for the Inverse Medium Problem in Scattering.
    ACM Transactions on Mathematical Software, 45(4), 45:1–45:20, 2019.

    DOI: 10.1145/3328525

  86. C. Büskens.
    A Mixed Open-Loop-Closed-Loop Strategy for Real-Time Optimization of Perturbed Optimal Control Problems with Constraints.
    ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 81, Supplement 2:243-244, 2001.
  87. C. Büskens.
    Echtzeitanpassung des klassischen Riccati-Reglers.
    at - Automatisierungstechnik, 57(6):269-278, Oldenbourg Wissenschaftsverlag, 2009.

    DOI: 10.1524/auto.2009.0775

  88. C. Büskens.
    Suboptimale Regelung nichtlinearer Prozesse.
    at - Automatisierungstechnik, 59(8):489-501, Oldenbourg Wissenschaftsverlag, 2011.

    DOI: 10.1524/auto.2011.0944

  89. C. Büskens, R. Baier, A. Chahma, M. Gerdts.
    Approximation of Reachable Sets by Direct Solution Methods of Optimal Control Problems.
    Optimization Methods and Software, 22(3):433-452, 2007.
  90. C. Büskens, M. Gerdts.
    Computation of Consistent Initial Values for Optimal Control Problems with DAE Systems of Higher Index.
    ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 81, Supplement 2:249-250, 2001.
  91. C. Büskens, M. Gerdts.
    Differentiability of Consistency Functions for DAE Systems.
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  158. K. Dethloff, A. Weisheimer, A. Rinke, D. Handorf, M. V. Kurgansky, W. Jansen, P. Maaß, P. Hupfer.
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  159. 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.
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  160. T. Dewenter, W. Heins, B. Werther, A. Hartmann, C. Bohn, H. Beck.
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  168. S. Dittmer, T. Kluth, M. Henriksen, P. Maaß.
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  170. S. Dobberschütz.
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  191. K. Flaßkamp, A. Ansari, T. Murphey.
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  199. M. Gehre, T. Kluth, C. Sebu, P. Maaß.
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  200. M. Gehre, T. Kluth, A. Lipponen, B. Jin, A. Seppänen, J. P. Kaipio, P. Maaß.
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    Journal of Computational and Applied Mathematics, 236(8):2126-2136, 2012.

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  201. J. Gehrt, R. Zweigel, S. Roy, C. Büskens, M. Kurowski, T. Jeinsch, A. Schubert, M. Gluch, O. Simanski, E. Pairet-Garcia, W. Bruhn, F. Diegel, D. Abel.
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  202. M. Gerdts, C. Büskens.
    Consistent Initialization of Sensitivity Matrices for a Class of Parametric DAE Systems .
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  206. 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.
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  207. C. Gottschalk, A. Koster, F. Liers, B. Peis, D. Schmand, A. Wierz.
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  208. S. Grützner, A. Muntean.
    Identifying processes governing damage evolution in quasi-static elasticity. Part 1 – Analysis.
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  209. H. Haddar, A. Konschin.
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  210. H. Haddar, A. Lechleiter, S. Marmorat.
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  211. H. Haddar, A. Lechleiter.
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  212. H. Haddar, A. Lechleiter.
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  213. E. Hairer, P. Maaß.
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  214. T. Harks, B. Peis, D. Schmand, B. Tauer, L. Vargas Koch.
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  215. N. Hase, S. M. Miller, P. Maaß, J. Notholt, M. Palm, T. Warneke.
    Atmospheric Inverse Modeling via Sparse Reconstruction.
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  216. T. Hein, K. Kazimierski.
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  217. E. Herrholz, D. Lorenz, G. Teschke, D. Trede.
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  218. A. Hinrichs, M. Piotrowski.
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  219. D. Hömberg, Q. Liu, J. Montalvo Urquizo, D. Nadolski, T. Petzold, A. Schmidt, A. Schulz.
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    Electronic Journal of Diff erential Equations, 2016(258):1-8, 2016.

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  221. M. Höpker, M. Böhm.
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  222. 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.
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  223. B. Jacob, B. Jin, T. Khan, P. Maaß.
    Optimal Source for Maximum Distinguishability in Optical Imaging.
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  224. M. Jahn, A. Luttmann, A. Schmidt, J. Paul.
    Finite element methods for problems with solid-liquid-solid phase transitions and free melt surface.
    PAMM, 12(1):403-404, Wiley, 2012.

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  225. M. Jahn, J. Montalvo Urquizo.
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  226. 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.

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  227. A. Janz, J. Schramm, M. Echim, F. Schrödel, C. Büskens.
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  228. M. Jiang, P. Maaß, T. Page.
    Regularizing properties of the Mumford-Shah functional for imaging applications.
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  229. Z. Jiang, H. Haddar, A. Lechleiter, M. El Guedri.
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    International Journal for Numerical Methods in Engineering, 89(3):337-353, 2012.

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  232. B. Jin, T. Khan, P. Maaß, M. Pidcock.
    Function Spaces and Optimal Currents in Impedance Tomography.
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    PAMM, 13(1), 473–474 S., WILEY-VCH, 2013.

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    Shrinkage versus Deconvolution.
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  258. E. Klann, P. Maaß, R. Ramlau.
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  259. O. Klein, F. Fogt, S. Hollerbach, G. Nebrich, T. Boskamp, A. Wellmann.
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    Proteomics - Clinical Applications, 190131 , Wiley, 2020.

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  260. 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.
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    Recent developments on system function/matrix representation, hybrid simulation techniques, and magnetic actuation.
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  262. T. Kluth, H. Albers.
    Simulation of non-linear magnetization effects and parameter identification problems in magnetic particle imaging.
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    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.

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    Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction.
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    Mathematical and Computer Modelling of Dynamical Systems, , Taylor & Francis, 2011.

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    IFAC-PapersOnLine, 50(1):9846-9851, 2017.

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  271. 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.

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  272. 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.

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  273. F. Kohlmai, V. Baumbach, C. Büskens, M. Knauer.
    Optimal routing of pipes in a virtual environment using nonlinear programming.
    International Journal of Fluid Power, , 2016.

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  274. 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.
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  276. A. Konschin.
    Numerical Scheme for Electromagnetic Scattering on Perturbed Periodic Inhomogeneous Media and Reconstruction of the Perturbation.
    SIAM Journal on Scientific Computing, 43(3), 21 S., SIAM, 2021.

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  277. A. Konschin, A. Lechleiter.
    Reconstruction of a Local Perturbation in Inhomogeneous Periodic Layers from Partial Near Field Measurements.
    Inverse Problems, 35(11), 114006, IOPscience, 2019.

    DOI: 10.1088/1361-6420/ab1c66
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  278. S. Kraft, M. Moser, C. Büskens, M. Echim.
    Echtzeitfähige Verbrennungssimulation eines Dual-Fuel-Motors für HiL-Anwendung.
    MTZ - Motortechnische Zeitschrift, 11, Springer Verlag, 2019.

    DOI: 10.1007/s35146-019-0115-1

  279. S. Kraft, M. Moser, C. Büskens, M. Echim.
    Real‑time capable combustion simulation of a dual‑fuel engine for hardware‑in‑the‑loop application.
    Heavy-Duty-, On- und Off-Highway-Motoren, :191-206, Springer Verlag, 2019.

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  280. N. H. Kröger, M. Böhm, M. Wolff.
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    Computational Materials Science, 64:30-33, Elsevier, 2012.

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  281. N. H. Kröger, M. Wolff, M. Böhm.
    On mathematical problems for viscoelastic multi-mechanism models in the isothermal case.
    ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, 96(5):550-569, 2016.

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  282. R. Kuhlmann.
    Learning to Steer Nonlinear Interior-Point Methods.
    EURO Journal on Computational Optimization, 7(4):381-419, 2019.

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  283. R. Kuhlmann, C. Büskens.
    A Primal-Dual Augmented Lagrangian Penalty-Interior-Point Filter Line Search Algorithm.
    Mathematical Methods of Operations Research, 87(3):451-483, 2018.

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  284. G. Kutyniok, W. Lim, R. Reisenhofer.
    ShearLab 3D: Faithful Digital Shearlet Transforms Based on Compactly Supported Shearlets.
    ACM Transactions on Mathematical Software (TOMS), 42(1):5:1-5:42, ACM, 2016.

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  285. M. Lachmann, J. Maldonado, W. Bergmann, F. Jung, M. Weber, C. Büskens.
    Self-Learning Data-Based Models as Basis of a Universally Applicable Energy Management System.
    Energies 2020, 13(8), 2084, 2020.

    DOI: 10.3390/en13082084

  286. 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

  287. E. Lakshtanov, A. Lechleiter.
    Difference Factorizations and Monotonicity in Inverse Medium Scattering for Contrasts with Fixed Sign on the Boundary .
    SIAM Journal on Mathematical Analysis, 48(6):3688-3707, SIAM, 2016.

    DOI: 10.1137/16M1060819
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  288. A. S. Lawless, N. Nichols, C. Böß, A. Bunse-Gerstner.
    Approximate Gauss-Newton methods for optimal state estimation using reduced order models.
    International Journal for Numerical Methods in Fluids, 56(8), 1367–1373, 2008.

    DOI: 10.1002/fld.1629

  289. A. S. Lawless, N. Nichols, C. Böß, A. Bunse-Gerstner.
    Using model reduction methods within four-dimensional variational data-assimilation.
    Monthly Weather Review, 136, 1511–1522, AMS - American Meteorological Society, 2008.

    DOI: 10.1175/2007MWR2103.1

  290. 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

  291. A. Lechleiter.
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    Inverse Problems, 22:1605-1625, IOPscience, 2006.

    DOI: 10.1088/0266-5611/22/5/006
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  292. A. Lechleiter.
    Explicit characterization of the support of non-linear inclusions.
    Inverse Problems and Imaging, 5:675-694, 2011.

    DOI: 10.3934/ipi.2011.5.675
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  293. A. Lechleiter.
    Imaging of Periodic Dielectrics.
    BIT Numerical Mathematics, 50:59-83, 2010.

    DOI: 10.1007/s10543-010-0255-7
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  294. A. Lechleiter.
    The factorization method is independent of transmission eigenvalues.
    Inverse Problems and Imaging, 3:123-138, 2009.

    DOI: 10.3934/ipi.2009.3.123
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  295. A. Lechleiter.
    The Floquet-Bloch Transform and Scattering from Locally Perturbed Periodic Surfaces.
    Journal of Mathematical Analysis and Applications, 446(1):605-627, 2017.

    online unter: http://arxiv.org/abs/1602.03349

  296. A. Lechleiter.
    The MUSIC Algorithm for Impedance Tomography of Small Inclusions from Discrete Data.
    Inverse Problems, 31(9), 095004, IOPscience, 2015.

    DOI: 10.1088/0266-5611/31/9/095004
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  297. A. Lechleiter, H. Haddar, Z. Jiang.
    Artificial boundary conditions for axisymmetric eddy current probe problems.
    Computers & Mathematics with Applications, 68(12):1844-1870, 2014.

    DOI: doi:10.1016/j.camwa.2014.10.008
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  298. A. Lechleiter, N. Hyvönen, H. Hakula.
    The factorization method applied to the complete electrode model of impedance tomography.
    SIAM Journal on Applied Mathematics, 68:1097-1121, 2008.

    DOI: 10.1137/070683295
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  299. 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
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  300. A. Lechleiter, D. Nguyen.
    A Trigonometric Galerkin Method for Volume Integral Equations Arising in TM Grating Scattering.
    Advances in Computational Mathematics, 40(1):1-25, Springer Verlag, 2014.

    DOI: 10.1007/s10444-013-9295-2
    online unter: Link

  301. A. Lechleiter, D. L. Nguyen.
    Factorization Method for Electromagnetic Inverse Scattering from Biperiodic Structures.
    SIAM Journal on Imaging Sciences, 6(2):1111-1139, SIAM, 2013.

    DOI: 10.1137/120903968
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  302. A. Lechleiter, D. L. Nguyen.
    On Uniqueness in Electromagnetic Scattering from Biperiodic Structures .
    ESAIM: Mathematical Modelling and Numerical Analysis, 47:1167-1184, 2013.

    DOI: 10.1051/m2an/2012063
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  303. A. Lechleiter, D. Nguyen.
    Scattering of Herglotz waves from periodic structures and mapping properties of the Bloch transform.
    Proceedings of the Royal Society of Edinburgh, Section: A Mathematics , 145(6):1283-1311, 2015.

    DOI: 10.1017/S0308210515000335

  304. A. Lechleiter, D. L. Nguyen.
    Spectral volumetric integral equation methods for acoustic medium scattering in a planar homogeneous 3D waveguide.
    IMA Journal of Numerical Analysis, 32(3):813-844, 2012.

    DOI: 10.1093/imanum/drr036
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  305. A. Lechleiter, D. L. Nguyen.
    Volume Integral Equations for Scattering from Anisotropic Diffraction Gratings.
    Mathematical Methods in the Applied Sciences, 36(3), 262–274 S., 2013.

    DOI: 10.1002/mma.2585
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  306. A. Lechleiter, S. Peters.
    Analytical Characterization and Numerical Approximation of Interior Eigenvalues for Impenetrable Scatterers from Far Fields.
    Inverse Problems, 4(30), 045006, IOPscience, 2014.

    DOI: 10.1088/0266-5611/30/4/045006
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  307. A. Lechleiter, S. Peters.
    Determining transmission eigenvalues of anisotropic inhomogeneous media from far field data.
    Communications in Mathematical Sciences, 13(7), 1803 – 1827, International Press, Boston, Massachusetts, USA, 2015.

    DOI: 10.4310/CMS.2015.v13.n7.a8
    online unter: http://www.intlpress.com/site/pub/pages/journals/items/cms/content/vols/0013/0007/a008/

  308. A. Lechleiter, M. Rennoch.
    Inside-outside duality and the determination of electromagnetic interior transmission eigenvalues.
    SIAM Journal on Mathematical Analysis, 47(1):684-705, SIAM, 2015.

    DOI: 10.1137/14098538X
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  309. A. Lechleiter, M. Rennoch.
    Non-linear Tikhonov Regularization in Banach Spaces for Inverse Scattering from Anisotropic Penetrable Media.
    Inverse Problems and Imaging, 11(1):151-176, 2017.

    DOI: 10.3934/ipi.2017008

  310. A. Lechleiter, A. Rieder.
    Newton regularizations for impedance tomography: a numerical study.
    Inverse Problems, 22:1967-1987, IOPscience, 2006.

    DOI: doi:10.1088/0266-5611/22/6/004
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  311. A. Lechleiter, A. Rieder.
    Newton regularizations for impedance tomography: convergence by local injectivity.
    Inverse Problems, 24, 065009, IOPscience, 2008.

    DOI: 10.1088/0266-5611/24/6/065009
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  312. A. Lechleiter, A. Rieder.
    Towards a general convergence theory for inexact Newton regularizations.
    Numerische Mathematik, 114:521-548, 2010.

    DOI: 10.1007/s00211-009-0256-0
    online unter: http://www.springerlink.com/content/hg8n3tq067143166/

  313. A. Lechleiter, T. Rienmüller.
    Collocation discretization for an integral equation in ocean acoustics with depth-dependent speed of sound.
    Mathematical Methods in the Applied Sciences, 40(5):1608-1624, Wiley, 2017.

    DOI: 10.1002/mma.4082

  314. A. Lechleiter, T. Rienmüller.
    Factorization Method for the Inverse Stokes Problem.
    Inverse Problems and Imaging, 7(4):1271-1293, 2013.

    DOI: doi:10.3934/ipi.2013.7.1271
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  315. A. Lechleiter, T. Rienmüller.
    Time-Harmonic Acoustic Wave Scattering in an Ocean with Depth-Dependent Sound Speed.
    Applicable Analysis - An International Journal, 95:978-999, 2015.

    DOI: 10.1080/00036811.2015.1047831

  316. A. Lechleiter, S. Ritterbusch.
    A variational method for scattering from penetrable rough layers.
    IMA Journal of Applied Mathematics, 75:366-391, 2010.

    DOI: 10.1093/imamat/hxp040
    online unter: http://imamat.oxfordjournals.org/content/75/3/366

  317. A. Lechleiter, J. Schlasche.
    Identifying Lame Parameters from Time-dependent Elastic Wave Measurements.
    Inverse Problems in Science and Engineering, 25(1):2-26, 2016.

    DOI: 10.1080/17415977.2015.1132713

  318. A. Lechleiter, R. Zhang.
    A Convergent Numerical Scheme for Scattering of Aperiodic Waves from Periodic Surfaces Based on the Floquet-Bloch Transform.
    SIAM Journal on Numerical Analysis, 55(2):713-736, 2017.

    DOI: 10.1137/16M1067524

  319. A. Lechleiter, R. Zhang.
    A Floquet-Bloch transform based numerical method for scattering from locally perturbed periodic surfaces.
    SIAM Journal on Scientific Computing, 39(5):B819-B839, 2017.

    DOI: 10.1137/16M1104111
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  320. A. Lechleiter, R. Zhang.
    Non-periodic acoustic and electromagnetic, scattering from periodic structures in 3D.
    Computers & Mathematics with Applications, 74(11): 2723-2738, 2017.

    online unter: https://doi.org/10.1016/j.camwa.2017.08.042

  321. A. Lechleiter, R. Zhang.
    Reconstruction of Local Perturbations in Periodic Surfaces.
    Inverse Problems, 035006 34(2018), IOPscience, 2018.

    DOI: doi.org/10.1088/1361-6420/aaa7b1

  322. 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

  323. 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 S., 2021.

    DOI: 10.3390/jimaging7030044
    online unter: https://www.mdpi.com/2313-433X/7/3/44

  324. 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

  325. J. Li, G. Sun, R. Zhang.
    The numerical solution of scattering by infinite rough interfaces based on the integral equation method.
    Computers & Mathematics with Applications, 71(7):1491-1502, 2016.

    online unter: https://ac.els-cdn.com/S0898122116300852/1-s2.0-S0898122116300852-main.pdf?_tid=83195944-b405-11e7-9068-00000aacb362&acdnat=1508332323_96d55a6d6c1263aa0750f01fce4f380f

  326. M. Li, R. Zhang.
    Near-field imaging of sound-soft obstacles in periodic waveguides .
    Inverse Problems and Imaging, 11(6):1091-1105, 2017.

    online unter: https://aimsciences.org/journals/displayArticlesnew.jsp?paperID=14621

  327. 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

  328. 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

  329. T. Linke, C. Büskens, S. Meier.
    Lattice Boltzmann Constraints for Standard Optimization Problems.
    PAMM, 13(1), 337–338 S., WILEY-VCH, 2013.

    DOI: 10.1002/pamm.201310164

  330. 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.
  331. 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 unter: arXiv.org e-Print archive

  332. 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 unter: arXiv.org e-Print archive

  333. 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

  334. 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

  335. 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

  336. 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

  337. 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

  338. 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.
  339. P. Maaß.
    Families of Orthogonal 2D Wavelets.
    SIAM Journal on Mathematical Analysis, 27(5):1454-1481, 1996.

    DOI: 10.1137/S003614109324649X

  340. P. Maaß.
    The Interior Radon Transform.
    SIAM Journal on Applied Mathematics, 52(3):710-724, 1992.

    DOI: 10.1137/0152040

  341. 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

  342. 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.
  343. P. Maaß.
    Wideband radar: the hyp transform .
    Inverse Problems, 5(5):849-857, IOPscience, 1989.

    DOI: 10.1088/0266-5611/5/5/012

  344. 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

  345. 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

  346. 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

  347. 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.
  348. 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

  349. 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

  350. 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.
  351. P. Maaß, R. Ramlau.
    Wavelet-accelerated regularization methods for hyperthermia treatment planning.
    International Journal of Imaging Systems and Technology, 7(3):191-199, 1996.
  352. 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

  353. 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

  354. 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

  355. P. Maaß, H. Stark.
    Wavelets and digital image processing.
    Surveys on Mathematics for Industry, 4(3):195-235, 1994.
  356. 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

  357. 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

  358. 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

  359. H. S. Mahato, M. Böhm.
    An existence result for a system of coupled semilinear diffusion-reaction equations with flux boundary conditions.
    European Journal of Applied Mathematics, 26:121-143, 2015.
  360. H. S. Mahato, M. Böhm.
    Global existence and uniqueness for a system of semilinear multi-species diffusion-reaction equations.
    The Journal of Applied Analysis and Computation, 3(4):357-376, 2013.

    online unter: http://jaac-online.com/index.php/jaac/article/view/173

  361. H. S. Mahato, M. Böhm.
    Homogenization of a system of semilinear diffusion-reaction equations in an H^{1,p} setting.
    Electronic Journal of Diff erential Equations, 210:1-22, 2013.

    online unter: http://ejde.math.txstate.edu/Volumes/2013/210/mahato.pdf

  362. H. S. Mahato, M. Böhm, S. Kräutle, P. Knabner.
    Upscaling of a system of semilinear parabolic partial differential equations coupled with a system of nonlinear ordinary differential equations originating in the context of crystal dissolution and precipitation inside a porous medium: existence theory ..
    Advances in Mathematical Sciences and Applications, 26:39-80, 2017.
  363. R. Mahnken , A. Schneidt, T. Antretter, U. Ehlenbröker, M. Wolff.
    Multi-scale modeling of bainitic phase transformation in multi-variant polycrystalline low alloy steels.
    International Journal of Solids and Structures, 54:156-171, 2015.
  364. R. Mahnken , M. Wolff, C. Cheng.
    A Multi-Mechanism Model for Cutting Simulations Combining Visco-plastic Asymmetry and Phase Transformation.
    International Journal of Solids and Structures, 50(20):3045-3066, Elsevier, 2013.

    DOI: 10.1016/j.ijsolstr.2013.05.008
    online unter: http://www.sciencedirect.com/science/article/pii/S0020768313002023

  365. R. Mahnken , M. Wolff, A. Schneidt, M. Böhm.
    Multi-Phase Transformations at Large Strains – Thermodynamic Framework and Simulation.
    International Journal of Plasticity, 39:1-26, Elsevier, 2012.

    DOI: 10.1016/j.ijplas.2012.05.009

  366. A. Mallek, D. Klosa, C. Büskens.
    Impact of Data Loss on Multi-Step Forecast of Traffic Flow in Urban Roads Using K-Nearest Neighbors.
    Sustainability, 14(18), 11232, 2022.

    DOI: https://doi.org/10.3390/su141811232

  367. D. Marpe, G. Blättermann, J. Ricke, P. Maaß.
    A Two-Layered Wavelet-Based Algorithm for Efficient Lossless and Lossy Image Compression.
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