Publications

Preprints

  • A. Habring and M. Holler. Neural-network-based regularization methods for inverse problems in imaging. Review paper, submitted for publication, arXiv:2312.14849, 2023. arXiv

  • A. Habring, M. Holler and T. Pock. Subgradient Langevin Methods for Sampling from Non-smooth Potentials. Submitted for publication, arXiv:2308.01417, 2023. arXiv

  • M. Holler, E. Morina and G. Schramm. Exact Parameter Identification in PET Pharmacokinetic Modeling Using the Irreversible Two Tissue Compartment Model. Submitted for publication, arXiv:2305.16989, 2023. arXiv

  • K. Bredies, M. Carioni, M. Holler, Y. Korolev and C.-B. Schönlieb. A sparse optimization approach to infinite infimal convolution regularization. Submitted for publication, arXiv:2304.08628, 2023. arXiv

Edited Books

  • P. Grohs, M. Holler, and A. Weinmann, editors. Handbook of Variational Methods for Nonlinear Geometric Data. Springer, 2020.

 Book Cover

Journal Articles

  • M. Holler, A. Schlüter and B. Wirth. Dimension reduction, exact recovery, and error estimates for sparse reconstruction in phase space. Applied and Computational Harmonic Analysis, 70:101631, 2024. Journal arXiv

  • M. Holler and B. Wirth. Exact reconstruction and reconstruction from noisy data with anisotropic total variation. To appear in SIAM Journal on Mathematical Analysis, 2023. arXiv

  • C. Aarset, A. Habring, M. Holler and M. Mitter. Unsupervised energy disaggregation via convolutional sparse coding. IEEE Transactions on Consumer Electronics, 2023. arXiv ,  IEEE

  • D. Narnhofer, A. Habring, M. Holler and T. Pock. Posterior-variance-based error quantification for inverse problems in imaging. SIAM Journal on Imaging Sciences, 17(1):301-333, 2024. arXiv ,  SIAM

  • C. Aarset, M. Holler and T. T. N. Nguyen. Learning-informed parameter identification in nonlinear time-dependent PDEs. Applied Mathematics and Optimization, 88(76), 2023. Open Access

  • A. Habring and M. Holler. A Note on the Regularity of Images Generated by Convolutional Neural Networks. SIAM Journal on Mathematics of Data Science, 5(3):670-692, 2023. arXiv ,  SIAM

  • W. J. Kern, S. Orlob, A. Bohn, W. Toller, J. Wnent, J.-T. Gräsner and M. Holler. Accelerometry-based classification of circulatory states during out-of-hospital cardiac arrest. IEEE Transactions on Biomedical Engineering, 70(8):2310-2317, 2023. arXiv ,  IEEE

  • G. Schramm and M. Holler. Fast and memory-efficient reconstruction of sparse Poisson data in listmode with non-smooth priors with application to time-of-flight PET. Physics in Medicine and Biology, 67(15):155020, 2022. arXiv ,  IOP

  • K. Bredies, M. Carioni and M. Holler. Regularization Graphs -- A unified framework for variational regularization of inverse problems. Inverse Problems, 38(10):105006, 2022. Open Access

  • S. Orlob, W. Kern, B. Alpers, M. Schörghuber, A. Bohn, M. Holler, J-T. Gräsner and J. Wnent. Chest compression fraction calculation: A new, automated, robust method to identify periods of chest compressions from defibrillator data - tested in Zoll X Series. Resuscitation, 172:162-169, 2022. Open Access

  • A. Habring, M. Holler. A Generative Variational Model for Inverse Problems in Imaging. SIAM Journal on Mathematics of Data Science 4(1):306-335, 2022. arXiv ,  SIAM

  • K. Bredies, M. Holler. Higher-order total variation approaches and generalisations. Topical Review. Inverse Problems, 36(12):123001, 2020. Open Access

  • A. Chambolle, M. Holler and T. Pock. A convex variational model for learning convolutional image atoms from incomplete data. Journal of Mathematical Imaging and Vision: Special Issue on Mathematics of Deep Learning, 62:417-444, 2020. Open Access

  • R. Huber, G. Haberfehlner, M. Holler, G. Kothleitner and K. Bredies. Total Generalized Variation regularization for multi-modal electron tomography. Nanoscale, 11:5617-5632, 2019. Open Access

  • A. Lesch, M. Schlögl, M. Holler, K. Bredies and R. Stollberger. Ultrafast 3D Bloch-Siegert B1+-mapping using variational modeling. Magnetic Resonance in Medicine, 81(2):881-892, 2019. Open Access

  • M. Holler, R. Huber and F. Knoll. Coupled regularization with multiple data discrepancies. Inverse Problems, 34(8):084003, 2018. Open Access

  • K. Bredies, M. Holler, M. Storath and A. Weinmann. Total Generalized Variation for manifold-valued data. SIAM Journal on Imaging Sciences, 11(3):1785-1848, 2018. PDF ,  SIAM

  • M. Hintermüller, M. Holler and K. Papafitsoros. A function space framework for structural total variation regularization with applications in inverse problems. Inverse Problems, 34(6):064002, 2018. Open Access

  • M. Holler and K. S. Kazimierski. Variational decompression of image data from DjVu encoded files. IEEE Transactions on Image Processing, 27(1):490-499, 2018. PDF

  • G. Schramm, M. Holler, A. Rezaei, K. Vunckx, F. Knoll, K. Bredies, F. Boada and J. Nuyts. Evaluation of parallel level sets and Bowsher's method as segmentation-free anatomical priors for time-of-flight PET reconstruction. IEEE Transactions on Medical Imaging, 37(2):590-603, 2018. PDF ,  IEEE

  • F. Knoll, M. Holler, T. Koesters, R. Otazo, K. Bredies and D. K. Sodickson. Joint MR-PET reconstruction using a multi-channel image regularizer. IEEE Transactions on Medical Imaging, 36(1):1-16, 2017. PDF

  • M. Schloegl, M. Holler, A. Schwarzl, K. Bredies and R. Stollberger. Infimal convolution of Total Generalized Variation functionals for dynamic MRI. Magnetic Resonance in Medicine, 78(1):142-155, 2017. PDF Open Access

  • A. Crozier, C. M. Augustin, A. Neic, A. J. Prassl, M. Holler, T. E. Fastl, A. Hennemuth, K. Bredies, T. Kuehne, M. J. Bishop, S. A. Niederer and G. Plank. Image-based personalization of cardiac anatomy for coupled electromechanical modeling. Annals of Biomedical Engineering, 44(1):58-70, 2016. Open Access

  • K. Bredies and M. Holler. A TGV-based framework for variational image decompression, zooming and reconstruction. Part I: Analytics. SIAM Journal on Imaging Sciences, 8(4):2814-2850, 2015. PDF

  • K. Bredies and M. Holler. A TGV-based framework for variational image decompression, zooming and reconstruction. Part II: Numerics. SIAM Journal on Imaging Sciences, 8(4):2851-2886, 2015. PDF

  • M. Holler and K. Kunisch. On infimal convolution of TV type functionals and applications to video and image reconstruction. SIAM Journal on Imaging Sciences, 7(4):2258-2300, 2014. PDF

  • K. Bredies and M. Holler. Regularization of linear inverse problems with total generalized variation. Journal of Inverse and Ill-posed Problems, 22(6):871-913, 2014. PDF

  • K. Bredies and M. Holler. A Total-Variation-based JPEG decompression model. SIAM Journal on Imaging Sciences, 5(1):366-393, 2012. PDF

Book Chapters

  • M. Holler and A. Weinmann. Non-smooth regularization for manifold-valued data. In P. Grohs, M. Holler, and A. Weinmann, editors, Handbook of Variational Methods for Nonlinear Geometric Data. Springer, 2020. PDF

Peer-Reviewed Proceedings Papers

  • A. Abdullah, M. Holler, K. Kunisch and M. Sabate Landman. Latent-Space Disentanglement with Untrained Generator Networks for the Isolation of Different Motion Types in Video Data. In: Scale Space and Variational Methods in Computer Vision, Springer LNCS, 14009:326-338, 2023. arXiv ,  Springer

  • G. Schramm, M. Holler, T. Koesters, F. Boada, F. Knoll, K. Bredies, and J. Nuyts. PET reconstruction with non-smooth gradient-based priors. In: Proceedings of the 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop (NSS/MIC/RTSD), 1-5, 2017. IEEE

  • F. Knoll, M. Holler, T. Koesters, K. Bredies, and D. K. Sodickson. Simultaneous PET-MRI reconstruction with vectorial second order total generalized variation. In: Proceedings of the 2015 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC), 1-4, 2016. IEEE

  • R. Huber, M. Holler, and K. Bredies. Graph-Laplacian minimisation for surface smoothing in 3D finite element tetrahedral meshes. In: Proceedings of the 1st OAGM-ARW Joint Workshop -- Vision Meets Robotics, 53-60, 2016. PDF

  • K. Bredies and M. Holler. Artifact-free variational MPEG decompression. Scale Space and Variational Methods in Computer Vision, Springer LNCS, 9087:216-228, 2015. PDF

  • K. Bredies and M. Holler. Artifact-free decompression and zooming of JPEG compressed images with total generalized variation. Computer Vision, Imaging and Computer Graphics. Theory and Application, Springer CCIS, 359:242-258, 2013. PDF

  • K. Bredies and M. Holler. A TGV regularized wavelet based zooming model. Scale Space and Variational Methods in Computer Vision, Springer LNCS, 7893:149-160, 2013. PDF

  • K. Bredies and M. Holler. Artifact-free JPEG decompression with total generalized variation. Proceedings of VISAPP 2012 - International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, pp. 12-21, 2012. PDF

Theses

  • M. Holler. Higher order regularization for model based data decompression. PHD Thesis, University of Graz, 2013 PDF

  • M. Holler. Theory and numerics for varational imaging. Artifact-free JPEG decompression and DCT based zooming. Masters Thesis, University of Graz, 2010. PDF

Unpublished

  • K. Bredies and M. Holler. A pointwise characterization of the subdifferential of the total variation functional. arXiv:1609.08918, 2016. PDF