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English

Markus Grasmair

Markus Grasmair

Førsteamanuensis
Institutt for matematiske fag

markus.grasmair@ntnu.no
Sentralbygg 2, 1052, Gløshaugen
Om Publikasjoner Undervisning

Om

Markus Grasmair er førsteamanuensis ved institutt for matematiske fag.

Se engelsk side for mer informasjon.

Kompetanseord

  • Anvendt matematikk

Publikasjoner

  • Kronologisk
  • Etter kategori
  • Se alle publikasjoner i Cristin

2022

  • Grasmair, Markus; Wøien, Esten Nicolai. (2022) A PDE-Based Method for Shape Registration. SIAM Journal of Imaging Sciences. volum 15 (2).
    Vitenskapelig artikkel
  • Langberg, Geir Severin Rakh Elvatun; Nygård, Jan Franz; Gogineni, Vinay Chakravarthi; Nygård, Mari; Grasmair, Markus; Naumova, Valeriya. (2022) Towards a data-driven system for personalized cervical cancer risk stratification. Scientific Reports. volum 12 (1).
    Vitenskapelig artikkel
  • Langberg, Geir Severin Rakh Elvatun; Stapnes, Mikal Solberg; Nygård, Jan Franz; Nygård, Mari; Grasmair, Markus; Naumova, Valeriya. (2022) Matrix factorization for the reconstruction of cervical cancer screening histories and prediction of future screening results. BMC Bioinformatics. volum 23.
    Vitenskapelig artikkel

2021

  • Gogineni, Vinay Chakravarthi; Langberg, Geir Severin Rakh Elvatun; Naumova, Valeriya; Nygård, Jan Franz; Nygård, Mari; Grasmair, Markus; Werner, Stefan. (2021) Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective. 2021 IEEE Statistical Signal Processing Workshop (SSP).
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
  • Grasmair, Markus; Naumova, Valeriya. (2021) Multiparameter Approaches in Image Processing. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging.
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

2020

  • Grasmair, Markus. (2020) Source Conditions for Non-Quadratic Tikhonov Regularization. Numerical Functional Analysis and Optimization.
    Vitenskapelig artikkel

2018

  • Grasmair, Markus; Klock, Timo; Naumova, Valeriya. (2018) Adaptive multi-penalty regularization based on a generalized Lasso path. Applied and Computational Harmonic Analysis.
    Vitenskapelig artikkel
  • Grasmair, Markus; Li, Housen; Munk, Axel. (2018) Variational multiscale nonparametric regression: Smooth functions. Annales de l'I.H.P. Probabilites et statistiques. volum 54 (2).
    Vitenskapelig artikkel
  • Grunert, Katrin; Holden, Helge; Grasmair, Markus. (2018) On the Equivalence of Eulerian and Lagrangian Variables for the Two-Component Camassa–Holm System. Current Research in Nonlinear Analysis: In Honor of Haim Brezis and Louis Nirenberg.
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

2017

  • Bauer, Martin; Eslitzbichler, Markus; Grasmair, Markus. (2017) Landmark-guided elastic shape analysis of human character motions. Inverse Problems and Imaging. volum 11 (4).
    Vitenskapelig artikkel

2016

  • Grasmair, Markus; Naumova, Valeriya. (2016) Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization. Inverse Problems. volum 32 (10).
    Vitenskapelig artikkel

2015

  • Bauer, Martin; Grasmair, Markus; Kirisits, Clemens. (2015) Optical Flow on Moving Manifolds. SIAM Journal of Imaging Sciences. volum 8 (1).
    Vitenskapelig artikkel

2014

  • Beretta, Elena; Grasmair, Markus; Muszkieta, Monika; Scherzer, Otmar. (2014) A variational algorithm for the detection of line segments. Inverse Problems and Imaging. volum 8 (2).
    Vitenskapelig artikkel

2013

  • Bauer, Martin; Fidler, Thomas; Grasmair, Markus. (2013) Local Uniqueness of the Circular Integral Invariant. Inverse Problems and Imaging. volum 7 (1).
    Vitenskapelig artikkel

2012

  • Frick, Klaus; Grasmair, Markus. (2012) Regularization of linear ill-posed problems by the augmented Lagrangian method and variational inequalities. Inverse Problems. volum 28 (10).
    Vitenskapelig artikkel

2011

  • Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2011) Necessary and sufficient conditions for linear convergence of l1-regularization. Communications on Pure and Applied Mathematics. volum 64 (2).
    Vitenskapelig artikkel

2010

  • Grasmair, Markus. (2010) Generalized Bregman distances and convergence rates for non-convex regularization methods. Inverse Problems. volum 26 (11).
    Vitenskapelig artikkel
  • Grasmair, Markus; Lenzen, Frank. (2010) Anisotropic total variation filtering. Applied Mathematics and Optimization. volum 62 (3).
    Vitenskapelig artikkel

2009

  • Scherzer, Otmar; Grasmair, Markus; Grossauer, Harald; Haltmeier, Markus; Lenzen, Frank. (2009) Variational methods in imaging. Springer. 2009. ISBN 978-0-387-30931-6. Applied mathematical sciences (167).
    Vitenskapelig monografi

2008

  • Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2008) Sparse regularization with l^q penalty term. Inverse Problems. volum 24 (5).
    Vitenskapelig artikkel

2007

  • Grasmair, Markus. (2007) The equivalence of the taut string algorithm and BV-regularization. Journal of Mathematical Imaging and Vision. volum 27 (1).
    Vitenskapelig artikkel

Tidsskriftspublikasjoner

  • Grasmair, Markus; Wøien, Esten Nicolai. (2022) A PDE-Based Method for Shape Registration. SIAM Journal of Imaging Sciences. volum 15 (2).
    Vitenskapelig artikkel
  • Langberg, Geir Severin Rakh Elvatun; Nygård, Jan Franz; Gogineni, Vinay Chakravarthi; Nygård, Mari; Grasmair, Markus; Naumova, Valeriya. (2022) Towards a data-driven system for personalized cervical cancer risk stratification. Scientific Reports. volum 12 (1).
    Vitenskapelig artikkel
  • Langberg, Geir Severin Rakh Elvatun; Stapnes, Mikal Solberg; Nygård, Jan Franz; Nygård, Mari; Grasmair, Markus; Naumova, Valeriya. (2022) Matrix factorization for the reconstruction of cervical cancer screening histories and prediction of future screening results. BMC Bioinformatics. volum 23.
    Vitenskapelig artikkel
  • Grasmair, Markus. (2020) Source Conditions for Non-Quadratic Tikhonov Regularization. Numerical Functional Analysis and Optimization.
    Vitenskapelig artikkel
  • Grasmair, Markus; Klock, Timo; Naumova, Valeriya. (2018) Adaptive multi-penalty regularization based on a generalized Lasso path. Applied and Computational Harmonic Analysis.
    Vitenskapelig artikkel
  • Grasmair, Markus; Li, Housen; Munk, Axel. (2018) Variational multiscale nonparametric regression: Smooth functions. Annales de l'I.H.P. Probabilites et statistiques. volum 54 (2).
    Vitenskapelig artikkel
  • Bauer, Martin; Eslitzbichler, Markus; Grasmair, Markus. (2017) Landmark-guided elastic shape analysis of human character motions. Inverse Problems and Imaging. volum 11 (4).
    Vitenskapelig artikkel
  • Grasmair, Markus; Naumova, Valeriya. (2016) Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization. Inverse Problems. volum 32 (10).
    Vitenskapelig artikkel
  • Bauer, Martin; Grasmair, Markus; Kirisits, Clemens. (2015) Optical Flow on Moving Manifolds. SIAM Journal of Imaging Sciences. volum 8 (1).
    Vitenskapelig artikkel
  • Beretta, Elena; Grasmair, Markus; Muszkieta, Monika; Scherzer, Otmar. (2014) A variational algorithm for the detection of line segments. Inverse Problems and Imaging. volum 8 (2).
    Vitenskapelig artikkel
  • Bauer, Martin; Fidler, Thomas; Grasmair, Markus. (2013) Local Uniqueness of the Circular Integral Invariant. Inverse Problems and Imaging. volum 7 (1).
    Vitenskapelig artikkel
  • Frick, Klaus; Grasmair, Markus. (2012) Regularization of linear ill-posed problems by the augmented Lagrangian method and variational inequalities. Inverse Problems. volum 28 (10).
    Vitenskapelig artikkel
  • Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2011) Necessary and sufficient conditions for linear convergence of l1-regularization. Communications on Pure and Applied Mathematics. volum 64 (2).
    Vitenskapelig artikkel
  • Grasmair, Markus. (2010) Generalized Bregman distances and convergence rates for non-convex regularization methods. Inverse Problems. volum 26 (11).
    Vitenskapelig artikkel
  • Grasmair, Markus; Lenzen, Frank. (2010) Anisotropic total variation filtering. Applied Mathematics and Optimization. volum 62 (3).
    Vitenskapelig artikkel
  • Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar. (2008) Sparse regularization with l^q penalty term. Inverse Problems. volum 24 (5).
    Vitenskapelig artikkel
  • Grasmair, Markus. (2007) The equivalence of the taut string algorithm and BV-regularization. Journal of Mathematical Imaging and Vision. volum 27 (1).
    Vitenskapelig artikkel

Bøker

  • Scherzer, Otmar; Grasmair, Markus; Grossauer, Harald; Haltmeier, Markus; Lenzen, Frank. (2009) Variational methods in imaging. Springer. 2009. ISBN 978-0-387-30931-6. Applied mathematical sciences (167).
    Vitenskapelig monografi

Del av bok/rapport

  • Gogineni, Vinay Chakravarthi; Langberg, Geir Severin Rakh Elvatun; Naumova, Valeriya; Nygård, Jan Franz; Nygård, Mari; Grasmair, Markus; Werner, Stefan. (2021) Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective. 2021 IEEE Statistical Signal Processing Workshop (SSP).
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
  • Grasmair, Markus; Naumova, Valeriya. (2021) Multiparameter Approaches in Image Processing. Handbook of Mathematical Models and Algorithms in Computer Vision and Imaging.
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
  • Grunert, Katrin; Holden, Helge; Grasmair, Markus. (2018) On the Equivalence of Eulerian and Lagrangian Variables for the Two-Component Camassa–Holm System. Current Research in Nonlinear Analysis: In Honor of Haim Brezis and Louis Nirenberg.
    Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Undervisning

Emner

  • TMA4180 - Optimering 1
  • TMA4183 - Optimering 2
  • TMA4130 - Matematikk 4N
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