Publikationen von Prof. Dr. Dirk Lorenz

Monografien (2)

1. K. Bredies, D. Lorenz.
   Mathematical Image Processing.
   Applied and Numerical Harmonic Analysis, Birkhäuser, 2018.

   DOI: 10.1007/978-3-030-01458-2

2. K. Bredies, D. Lorenz.
   Mathematische Bildverarbeitung:.
   , Vieweg Verlag, 2011.

Buchkapitel (6)

1. N. Breustedt, P. Climaco, J. Garcke, J. Hamaekers, D. Lorenz, G. Kutyniok, R. Oerder, C. V. Shukla.
   On the interplay of subset selection and informed graph neural networks.
   Informed Machine Learning, Springer Verlag, 2025.

   DOI: 10.1007/978-3-031-83097-6
   online unter: https://arxiv.org/abs/2306.10066

2. E. Herrholz, D. Lorenz, G. Teschke, D. Trede.
   Sparsity and compressed sensing in inverse problems.
   Extraction of Quantifiable Information from Complex Systems, S. Dahlke, W. Dahmen, M. Griebel, W. Hackbusch, K. Ritter, R. Schneider, C. Schwab, H. Yserentant (Hrsg.), Lecture Notes in Computational Science and Engineering, S. 365-379, Springer Verlag, 2014.
3. 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 (Hrsg.), S. 379-392, Springer Verlag, 2010.

   DOI: 10.1007/978-3-642-11248-5_20

4. 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 (Hrsg.), S. 75-109, Springer Verlag, 2008.
5. 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 (Hrsg.), acatech DISKUTIERT, S. 461-477, acatech - Deutsche Akademie der Technikwissenschaften, 2008.

   DOI: 10.1007/978-3-540-89435-3_20

6. 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 (Hrsg.), 5266, S. 84-93, SPIE, 2004.

   DOI: 10.1117/12.515945

Zeitschriftenartikel (75)

1. D. Lorenz, M. Winkler.
   Minimal error momentum Bregman-Kaczmarz.
   Linear Algebra and its Applications, 709:416-448, Elsevier, 2025.

   DOI: 10.1016/j.laa.2025.01.024
   online unter: https://arxiv.org/abs/2307.15435

2. D. Lorenz, E. Bednarczuk, T. H. Tran.
   Proximal Algorithms for a class of abstract convex functions.
   Set-Valued and Variational Analysis, 33(5):1-44, Springer Verlag, 2025.

   DOI: 10.1007/s11228-025-00743-9
   online unter: https://arxiv.org/abs/2402.17072

3. R. Gower, D. Lorenz, M. Winkler.
   A Bregman-Kaczmarz method for nonlinear systems of equations.
   Computational Optimization and Applications, 87:1059-1098, 2024.

   DOI: 10.1007/s10589-023-00541-9
   online unter: https://arxiv.org/abs/2303.08549

4. L. Tondji, I. Necoara, D. Lorenz.
   Acceleration and restart for the randomized Bregman-Kaczmarz method.
   Linear Algebra and its Applications, 699:508-538, 2024.

   DOI: 10.1016/j.laa.2024.07.009
   online unter: https://arxiv.org/abs/2310.17338

5. L. Tondji, I. Tondji, D. Lorenz.
   Adaptive Bregman-Kaczmarz: An approach to solve linear inverse problems with independent noise exactly.
   Inverse Problems, 40(9), 095006, IOPscience, 2024.

   DOI: 10.1088/1361-6420/ad5fb1
   online unter: https://arxiv.org/abs/2309.06186

6. C. Brauer, N. Breustedt, T. de Wolff, D. Lorenz.
   Learning variational models with unrolling and bilevel optimization.
   Analysis and Applications, 22(3):569-617, World Scientific, 2024.

   DOI: 10.1142/S0219530524400037
   online unter: https://arxiv.org/abs/2209.12651

7. D. Lorenz, J. Marquardt, E. Naldi.
   The degenerate variable metric proximal point algorithm and adaptive stepsizes for primal-dual Douglas-Rachford.
   Optimization, :1-27, Taylor & Francis, 2024.

   DOI: 10.1080/02331934.2024.2325552
   online unter: https://arxiv.org/abs/2302.13128

8. D. Lorenz, F. Schneppe.
   Chambolle-Pock’s primal-dual method with mismatched adjoint.
   Applied Mathematics & Optimization, 87(22), 2023.

   DOI: 10.1007/s00245-022-09933-5
   online unter: https://arxiv.org/abs/2201.04928

9. N. K. Bellam Muralidhar, C. Gräßle, N. Rauter, A. Mikhaylenko, R. Lammering, D. Lorenz.
   Damage identification in fiber metal laminates using bayesian analysis with model order reduction.
   Computer Methods in Applied Mechanics and Engineering, Part B 403, 2023.

   DOI: 10.1016/j.cma.2022.115737
   online unter: https://arxiv.org/abs/2206.04329

10. D. Lorenz, F. Schneppe, L. Tondji.
    Linearly convergent adjoint free solution of least squares problems by random descent.
    Inverse Problems, 39(12), 125019, 2023.

    DOI: 10.1088/1361-6420/ad08ed
    online unter: https://arxiv.org/abs/2306.01946

11. A. Ebner, J. Frikel, D. Lorenz, J. Schwab, M. Haltmeier.
    Regularization of inverse problems by filtered diagonal frame decomposition.
    Applied and Computational Harmonic Analysis, 62:66-83, 2023.

    DOI: 10.1016/j.acha.2022.08.005
    online unter: https://arxiv.org/abs/2008.06219

12. K. Bredies, E. Chenchene, D. Lorenz, E. Naldi.
    Degenerate preconditioned proximal point algorithms.
    SIAM Journal on Optimization, 32(3), 2022.

    DOI: 10.1137/21M1448112
    online unter: https://arxiv.org/abs/2109.11481

13. F. Schöpfer, D. Lorenz, L. Tondji, M. Winkler.
    Extended randomized Kaczmarz method for sparse least squares and impulsive noise problems.
    Linear Algebra and its Applications, 652:132-154, 2022.

    DOI: 10.1016/j.laa.2022.07.003
    online unter: https://arxiv.org/abs/2201.08620

14. D. Lorenz, L. Tondji.
    Faster randomized block sparse Kaczmarz by averaging.
    Numerical Algorithms, 91:1417-1451, 2022.

    DOI: 10.1007/s11075-022-01473-x
    online unter: https://arxiv.org/abs/2203.10838

15. D. Ghilli, D. Lorenz, E. Resmerita.
    Nonconvex flexible sparsity regularization: theory and monotone numerical schemes.
    Optimization, 71(4):1114-1140, 2022.

    DOI: 10.1080/02331934.2021.2011869
    online unter: https://arxiv.org/abs/2111.06281

16. A. Mikhaylenko, N. Rauter, N. K. Bellam Muralidhar, T. Barth, D. Lorenz, R. Lammering.
    Numerical analysis of the main wave propagation characteristics in a steel-CFRP laminate including model order reduction.
    Acoustics, 4(3):517-537, 2022.

    DOI: 10.3390/acoustics4030032
    online unter: https://arxiv.org/abs/2206.04329

17. D. Lorenz, H. Mahler.
    Orlicz space regularization of continuous optimal transport problems.
    Applied Mathematics & Optimization, 85(14), 2022.

    DOI: 10.1007/s00245-022-09826-7
    online unter: https://arxiv.org/abs/2004.11574

18. C. Clason, D. Lorenz, H. Mahler, B. Wirth.
    Entropic regularization of continuous optimal transport problems.
    Journal of Mathematical Analysis and Applications, 494(1), 2021.

    DOI: 10.1016/j.jmaa.2020.124432
    online unter: http://arxiv.org/abs/1803.02848

19. F. Schneppe, D. Lorenz.
    Parameter estimation for orthogonal polynomial moments.
    PAMM, 20(1), Wiley, 2021.

    DOI: 10.1002/pamm.202000253

20. N. K. Bellam Muralidhar, N. Rauter, A. Mikhaylenko, R. Lammering, D. Lorenz.
    Parametric model order reduction of guided ultrasonic wave propagation in fiber metal laminates with damage.
    Modelling, 2(4):591-608, 2021.

    DOI: 10.3390/modelling2040031
    online unter: https://www.preprints.org/manuscript/202109.0312/v1

21. D. Lorenz, C. Meyer, P. Manns.
    Quadratically regularized optimal transport.
    Applied Mathematics & Optimization, 83:1919-1949, 2021.

    DOI: 10.1007/s00245-019-09614-w
    online unter: https://arxiv.org/abs/1903.01112

22. C. Brauer, D. Lorenz.
    Complexity and applications of the homotopy principle for uniformly constrained sparse minimization.
    Applied Mathematics & Optimization, 82(3):1-34, 2020.

    DOI: 10.1007/s00245-019-09565-2

23. B. Komander, D. Lorenz, L. Vestweber.
    Denoising of image gradients and total generalized variation denoising.
    Journal of Mathematical Imaging and Vision, 61(1):21-39, 2019.

    DOI: 10.1007/s10851-018-0819-8
    online unter: http://arxiv.org/abs/1712.08585

24. F. Schöpfer, D. Lorenz.
    Linear convergence of the Randomized Sparse Kaczmarz method.
    Mathematical Programming, 173(1):509-536, 2019.

    DOI: 10.1007/s10107-017-1229-1
    online unter: http://arxiv.org/abs/1610.02889

25. D. Lorenz, Q. Tran-Dinh.
    Non-stationary Douglas-Rachford and alternating direction method of multipliers: adaptive stepsizes and convergence.
    Computational Optimization and Applications, 74(1):67-92, 2019.

    DOI: 10.1007/s10589-019-00106-9
    online unter: http://arxiv.org/abs/1801.03765

26. C. Brauer, D. Lorenz, A. Tillmann.
    A primal-dual homotopy algorithm for ℓ1 -minimization with ℓ∞ -constraints.
    Computational Optimization and Applications, 70:443-478, 2018.

    DOI: 10.1007/s10589-018-9983-4
    online unter: http://arxiv.org/abs/1601.10022

27. D. Lorenz, L. M. Mescheder.
    An extended Perona-Malik model based on probabilistic models.
    Journal of Mathematical Imaging and Vision, 60(1):128-144, 2018.

    DOI: 10.1007/s10851-017-0746-0
    online unter: http://arxiv.org/abs/1612.06176

28. D. Lorenz, K. Wirths.
    Sarrus rules for matrix determinants and dihedral groups.
    The College Mathematics Journal, 49(5):333-340, 2018.

    DOI: 10.1080/07468342.2018.1526019
    online unter: https://arxiv.org/abs/1809.08948

29. D. Lorenz, S. Rose, F. Schöpfer.
    The randomized Kaczmarz method with mismatched adjoint.
    BIT Numerical Mathematics, 48(4):1079-1098, 2018.

    DOI: 10.1007/s10543-018-0717-x
    online unter: http://arxiv.org/abs/1803.02848

30. D. Lorenz, J. Lorenz, C. Brauer.
    Rank-optimal weighting or “How to be best in the OECD Better Life Index?”.
    Social Indicators Research, 134:75-92, 2017.

    DOI: 10.1007/s11205-016-1416-0
    online unter: http://arxiv.org/abs/1608.04556

31. D. Lorenz, E. Resmerita.
    Flexible sparse regularization.
    Inverse Problems, 33(1), 2016.

    DOI: 10.1088/0266-5611/33/1/014002
    online unter: http://arxiv.org/abs/1601.04429

32. D. Lorenz, T. Pock.
    An inertial forward-backward method for monotone inclusions.
    Journal of Mathematical Imaging and Vision, 51(1):311-325, 2015.

    DOI: 10.1007/s10851-014-0523-2
    online unter: http://arxiv.org/abs/1403.3522

33. D. Lorenz, C. Kruschel.
    Computing and analyzing recoverable supports for sparse reconstruction.
    Advances in Computational Mathematics, 41(6):1119-1144, 2015.

    DOI: 10.1007/s10444-015-9403-6
    online unter: http://arxiv.org/abs/1309.2460

34. D. Lorenz, K. Bredies, S. Reiterer.
    Minimization of non-smooth, non- convex functionals by iterative thresholding.
    Journal of Optimization Theory and Applications, 165(1):78-112, 2015.

    DOI: 10.1007/s10957-014-0614-7

35. D. Lorenz, A. Tillmann, M. E. Pfetsch.
    Solving basis pursuit: Subgra- dient algorithm, heuristic optimality check, and solver comparison.
    ACM Transactions on Mathematical Software (TOMS), 41(2), 2015.

    DOI: 10.1145/2689662
    online unter: http://www.optimization-online.org/DB_HTML/2011/07/3100.html

36. D. Lorenz, A. Tillmann, M. E. Pfetsch.
    An infeasible-point subgradient method using adaptive approximate projections.
    Computational Optimization and Applications, 57(2):271-306, 2014.

    DOI: 10.1007/s10589-013-9602-3
    online unter: http://arxiv.org/abs/1104.5351

37. D. Lorenz, B. Komander, M. Fischer, M. Petz, R. Tutsch.
    Data fusion of surface normals and point coordinates for deflectometric measurements.
    Journal of Sensors and Sensor Systems, 3:281-290, 2014.

    DOI: 10.5194/jsss-3-281-2014

38. D. Lorenz, J. Lellmann, C. Schönlieb, T. Valkonen.
    Imaging with Kantorovich-Rubinstein discrepancy.
    SIAM Journal on Imaging Sciences, 7(4):2833-2859, 2014.

    DOI: 10.1137/140975528
    online unter: http://arxiv.org/abs/1407.0221

39. D. Lorenz, M. Matz, K. Schumacher, K. Hatlapatka, K. Baumann.
    Observer-independent quantification of insulin granule exocytosis and pre-exocytotic mobility by TIRF microscopy.
    Microscopy and Microanalysis, 20(1):206-218, 2014.

    DOI: 10.1017/S1431927613013767

40. 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

41. D. Lorenz, C. Kruschel, J. S. Jørgensen.
    Testable uniqueness conditions for empirical assessment of undersampling levels in total variation-regularized x-ray CT.
    Inverse Problems in Science and Engineering, 23:1283-1305, 2014.

    DOI: 10.1080/17415977.2014.986724
    online unter: http://arxiv.org/abs/1409.0214

42. D. Lorenz, S. Wenger, F. Schöpfer.
    The linearized Bregman method via split feasibility problems: Analysis and generalizations.
    SIAM Journal on Imaging Sciences, 2(7), 2014.

    DOI: 10.1137/130936269
    online unter: http://arxiv.org/abs/1309.2094

43. D. Lorenz.
    Constructing test instances for basis pursuit denoising.
    IEEE Transactions of Signal Processing, 61(5):1210-1214, 2013.

    DOI: 10.1109/TSP.2012.2236322
    online unter: http://arxiv.org/abs/1103.2897

44. D. Lorenz, S. Wenger, M. Magnor.
    Fast image-based modeling of astronomical nebulae.
    Computer Graphics Forum, 32(7), 2013.
45. D. Lorenz, N. Worliczek.
    Necessary conditions for variational regularization schemes.
    Inverse Problems, 29, 075016, 2013.

    DOI: 10.1088/0266-5611/29/7/075016
    online unter: http://arxiv.org/abs/1204.0649

46. 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.
47. D. Lorenz, S. Wenger, M. Ament, S. Guthe, A. Tillmann, D. Weiskopf, M. Magnor.
    Visualization of astronomical nebulae via distributed multi-gpu compressed sensing tomography.
    IEEE Transactions on Visualization and Computer Graphics, 18(12):2188-2197, 2012.

    DOI: 10.1109/TVCG.2012.281

48. 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

49. D. Lorenz, K. Chen.
    Image sequence interpolation using optimal control.
    Journal of Mathematical Imaging and Vision, 41(3):222-238, 2011.

    DOI: 10.1007/s10851-011-0274-2
    online unter: http://arxiv.org/abs/1008.0548

50. D. Lorenz, E. Resmerita, K. Frick.
    Morozov’s principle for the augmented Lagrangian method applied to linear inverse problems.
    Multiscale Modeling & Simulation, 9(4):1528-1548, 2011.

    DOI: 10.1137/100812835
    online unter: http://arxiv.org/abs/1010.5181

51. D. Lorenz.
    A projection proximal-point algorithm for ℓ¹ -minimization.
    Numerical Functional Analysis and Optimization, 31(2):172-190, 2010.

    DOI: 10.1080/01630560903381712
    online unter: http://arxiv.org/abs/0904.1523

52. D. Lorenz, A. Rösch.
    Error estimates for joint Tikhonov- and Lavrentiev-regularization of constrained control problems.
    Applicable Analysis - An International Journal, 89(11):1679-1692, 2010.

    DOI: 10.1080/00036811.2010.496360
    online unter: http://arxiv.org/abs/0909.4648

53. D. Lorenz, B. Jin.
    Heuristic parameter-choice rules for convex variational regularization based on error estimates.
    SIAM Journal on Numerical Analysis, 48(3):1208-1229, 2010.

    DOI: 10.1137/100784369
    online unter: http://arxiv.org/abs/1001.5346

54. D. Lorenz, K. Chen.
    Image sequence interpolation based on optical flow, segmentation, and optimal control.
    IEEE Transactions on Image Processing, 21(3):1020-1030, 2010.

    DOI: 10.1109/TIP.2011.2179305

55. D. Lorenz, J. Lorenz.
    On conditions for convergence to consensus.
    IEEE Transactions on Automatic Control, 55(7):1651-1656, 2010.

    DOI: 10.1109/TAC.2010.2046086
    online unter: http://arxiv.org/abs/0803.2211

56. 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

57. 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

58. 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 unter: arXiv.org e-Print archive

59. 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 unter: HAL (Hyper Articles en Ligne) open archive

60. D. Lorenz.
    On the role of sparsity in inverse problems.
    Journal of Inverse and Ill-posed Problems, 17(1):69-76, 2009.

    DOI: 10.1515/JIIP.2009.007

61. D. Lorenz, K. Bredies.
    Regularization with non-convex separable constraints.
    Inverse Problems, 25(8), 085011, 2009.

    DOI: 10.1088/0266-5611/25/8/085011

62. 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 unter: http://dx.doi.org/10.1088/0266-5611/24/3/035007

63. D. Lorenz.
    Convergence rates and source conditions for Tikhonov regularization with sparsity constraints.
    Journal of Inverse and Ill-posed Problems, 16(5):463-478, 2008.

    DOI: 10.1515/JIIP.2008.025
    online unter: http://dx.doi.org/10.1515/JIIP.2008.025

64. K. Bredies, D. Lorenz.
    Iterated hard shrinkage for minimization problems with sparsity constraints.
    SIAM Journal on Scientific Computing, 30(2):657-683, 2008.
65. 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

66. 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.
67. 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

68. 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.
69. 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.
70. 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

71. D. Lorenz.
    Non-convex variational denoising of images: Interpolation between hard and soft wavelet shrinkage.
    Current Developments in Theory and Applications of Wavelets, 1(1):31-56, 2007.
72. 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

73. D. Lorenz.
    Solving variational methods in image processing via projections - a common view on T V -denoising and wavelet shrinkage.
    Zeitschrift für angewandte Mathematik und Mechanik, 87(1):247-256, 2007.

    DOI: 10.1002/zamm200610300

74. 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

75. 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

Preprints (6)

1. J. Bresch, D. Lorenz, F. Schneppe, M. Winkler.
   Computing adjoint mismatch of linear maps.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2503.21361

2. M. M. Alves, D. Lorenz, E. Naldi.
   A general framework for inexact splitting algorithms with relative errors and applications to Chambolle-Pock and Davis-Yin methods.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2407.05893

3. J. Bresch, D. Lorenz, F. Schneppe, M. Winkler.
   Matrix-free stochastic calculation of operator norms without using adjoints.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2410.08297

4. D. Lorenz, M. Winkler, A. Leitão, J. C. Rabelo.
   On inertial Levenberg-Marquardt type methods for solving nonlinear ill-posed operator equations.
   Zur Veröffentlichung eingereicht.

   online unter: https://arxiv.org/abs/2406.07044

5. K. Chen, D. Lorenz.
   Image Sequence Interpolation based on Optical Flow, Segmentation, and Optimal Control.
   Berichte aus der Technomathematik 11-11, Universität Bremen, 2011.
6. K. Chen, D. Lorenz.
   Image sequence interpolation using optimal control.
   Berichte aus der Technomathematik 11-01, Universität Bremen, 2011.

Tagungsbeiträge (24)

1. L. Tondji, D. Lorenz, I. Necoara.
   An accelerated randomized Bregman-Kaczmarz method for strongly convex linearly constraint optimization.
   2023 European Control Conference (ECC).
   

   DOI: 10.23919/ECC57647.2023.10178390

2. C. Brauer, D. Lorenz, L. Tondji.
   Group equivariant networks for leakage detection in vacuum bagging.
   30th European Signal Processing Confer- ence, EUSIPCO 2022.
   

   online unter: https://eurasip.org/Proceedings/Eusipco/Eusipco2022/pdfs/0001437.pdf

3. N. K. Bellam Muralidhar, D. Lorenz.
   A model-based damage identification using guided ultrasonic wave propagation in fiber metal laminates.
   VI ECCOMAS Young Investigators Conference YIC2021.
   
4. C. Brauer, D. Lorenz.
   Ergodic bilevel oprimization.
   SPARS 2019.
   
5. C. Brauer, D. Lorenz, A. Tillmann.
   Exact recovery of partially sparse vectors.
   SPARS 2019.
   
6. D. Lorenz, E. Resmerita.
   Flexible sparse regularization with general non-convex penalties.
   SPARS 2019.
   
7. C. Brauer, Z. Zhao, D. Lorenz, T. Fingscheidt.
   Learning to dequantize speech signals by primal-dual networks: an approach for acoustic sensor networks.
   IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
   

   DOI: 10.1109/ICASSP.2019.8683341

8. D. Lorenz, H. Mahler.
   Orlicz-space regularization for optimal transport and algorithms for quadratic regularization.
   NeurIPS Workshop on Optimal Transport and Machine Learning, Vancouver, Kanada.
   

   online unter: https://arxiv.org/abs/1909.06082

9. C. Brauer, C. Clason, D. Lorenz, B. Wirth.
   A Sinkhorn-Newton method for entropic optimal transport.
   NIPS Workshop on Optimal Transport and Machine Learning.
   

   online unter: http://arxiv.org/abs/171006635

10. B. Komander, D. Lorenz.
    Denoising of image gradients and constrained total generalized variation.
    International Conference on Scale Space and Variational Methods in Computer Vision,.
    

    DOI: 10.1007/978-3-319-58771-4_35

11. C. Brauer, D. Lorenz, T. Gerkmann.
    Sparse reconstruction of quantized speech signals.
    IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
    

    DOI: 10.1109/ICASSP.2016.7472817

12. C. Brauer, D. Lorenz.
    Cartoon-texture-noise decomposition with transport norms.
    Scale Space and Variational Methods.
    LNCS, S. 142-153, Springer Verlag, 2015.

    DOI: 10.1007/978-3-319-18461-6_12

13. D. Lorenz, F. Schöpfer, S. Wenger, M. Magnor.
    sparse Kaczmarz solver and a linearized Bregman method for online compressed sensing.
    IEEE International Conference on Image Processing.
    

    Recognized as one of the “Top 10%” papers

    DOI: 10.1109/ICIP.2014.7025269
    online unter: http://arxiv.org/abs/1403.7543

14. D. Lorenz, E. Laue.
    Variational methods for motion deblurring with still background.
    Scale Space and Variational Methods.
    LNCS, A. Kuijper, T. Pock, K. Bredies, H. Bischof (Hrsg.), 7893:74-85, Springer Verlag, 2013.

    DOI: 10.1007/978-3-642-38267-3_7

15. 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, Frankreich.
    

    online unter: http://hal.inria.fr/inria-00369397/en/

16. D. Lorenz, J. Lorenz.
    Convergence to consensus by general averaging.
    POSTA 09.
    Lecture Notes in Control and Information Sciences , B. Rafael, S. Romero (Hrsg.), S. 91-100, Springer Verlag, 2009.

    DOI: 10.1007/978-3-642-02894-6_9

17. 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, Frankreich.
    
18. 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, Türkei.
    Journal of Inverse and Ill-Posed Problems, 17(1):69-76, 2009.

    DOI: 10.1515/JIIP.2009.008

19. D. Lorenz, K. Bredies.
    Iterated hard-thresholding for linear inverse prob- lems with sparsity constraints.
    PAMM.
    Proceedings in Applied Mathematics and Mechanics, S. 2060061-2060062, 2008.
20. 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, Großbritannien.
    Erscheint in Proceedings of 15th European Conference on Mathematics in Industry'08.
21. 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, Deutschland.
    Proceedings in Applied Mathematics and Mechanics, 8(1):10941-10942, 2008.

    DOI: 10.1002/pamm.200810941

22. 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

23. 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.
    
24. C. Brauer, D. Lorenz, L. Tondji.
    Group equivariant networks for leakage detection in vacuum bagging.
    30th European Signal Processing Confer- ence, EUSIPCO 2022.
    

    online unter: https://eurasip.org/Proceedings/Eusipco/Eusipco2022/pdfs/0001437.pdf