Markus Grasmair
Markus Grasmair
Department of Mathematical Sciences, NTNU Trondheim
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Cited by
Cited by
Variational methods in imaging, volume 167 of Applied Mathematical Sciences
O Scherzer, M Grasmair, H Grossauer, M Haltmeier, F Lenzen
Springer, New York, 2009
Sparse regularization with lq penalty term
M Grasmair, M Haltmeier, O Scherzer
Inverse Problems 24 (5), 055020, 2008
Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering
T Alexandrov, M Becker, S Deininger, G Ernst, L Wehder, M Grasmair, ...
Journal of proteome research 9 (12), 6535-6546, 2010
Necessary and sufficient conditions for linear convergence of ℓ1‐regularization
M Grasmair, O Scherzer, M Haltmeier
Communications on Pure and Applied Mathematics 64 (2), 161-182, 2011
Anisotropic total variation filtering
M Grasmair, F Lenzen
Applied Mathematics & Optimization 62 (3), 323-339, 2010
Generalized Bregman distances and convergence rates for non-convex regularization methods
M Grasmair
Inverse Problems 26 (11), 115014, 2010
Locally adaptive total variation regularization
M Grasmair
International Conference on Scale Space and Variational Methods in Computer …, 2009
Non-convex sparse regularisation
M Grasmair
Journal of Mathematical Analysis and Applications 365 (1), 19-28, 2010
The equivalence of the taut string algorithm and BV-regularization
M Grasmair
Journal of Mathematical Imaging and Vision 27 (1), 59-66, 2007
The residual method for regularizing ill-posed problems
M Grasmair, M Haltmeier, O Scherzer
Applied Mathematics and Computation 218 (6), 2693-2710, 2011
Linear convergence rates for Tikhonov regularization with positively homogeneous functionals
M Grasmair
Inverse Problems 27 (7), 075014, 2011
Well-posedness and convergence rates for sparse regularization with sublinear penalty term
M Grasmair
Inverse Problems & Imaging 3 (3), 383, 2009
Variational inequalities and higher order convergence rates for Tikhonov regularisation on Banach spaces
M Grasmair
Journal of Inverse and Ill-Posed Problems 21 (3), 379-394, 2013
Landmark-guided elastic shape analysis of human character motions
M Bauer, M Eslitzbichler, M Grasmair
arXiv preprint arXiv:1502.07666, 2015
Regularization of linear ill-posed problems by the augmented Lagrangian method and variational inequalities
K Frick, M Grasmair
Inverse problems 28 (10), 104005, 2012
Variational multiscale nonparametric regression: Smooth functions
M Grasmair, H Li, A Munk
Annales de l'Institut Henri Poincaré, Probabilités et Statistiques 54 (2 …, 2018
Applied mathematical sciences.
O Scherzer, M Grasmair, H Grossauer
Variational methods in imaging 167, 2009
A non-convex PDE scale space
M Grasmair, F Lenzen, A Obereder, O Scherzer, M Fuchs
International Conference on Scale-Space Theories in Computer Vision, 303-315, 2005
Identifiability and reconstruction of shapes from integral invariants
T Fidler, M Grasmair, O Scherzer
Inverse Problems & Imaging 2 (3), 341, 2008
Shape reconstruction with a priori knowledge based on integral invariants
T Fidler, M Grasmair, O Scherzer
SIAM Journal on Imaging Sciences 5 (2), 726-745, 2012
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