Markus Grasmair

According to our database, Markus Grasmair authored at least 20 papers between 2005 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

Maximum Discrepancy Generative Regularization and Non-Negative Matrix Factorization for Single Channel Source Separation.

Martin Ludvigsen, Markus Grasmair

CoRR, 2024

Parameter identification in PDEs by the solution of monotone inclusion problems.

Pankaj Gautam, Markus Grasmair

CoRR, 2024

2023

Adversarial Generative NMF for Single Channel Source Separation.

Martin Ludvigsen, Markus Grasmair

CoRR, 2023

2022

A PDE-Based Method for Shape Registration.

Esten Nicolai Wøien, Markus Grasmair

SIAM J. Imaging Sci., 2022

A square root velocity framework for curves of bounded variation.

Markus Grasmair

CoRR, 2022

Matrix factorization for the reconstruction of cervical cancer screening histories and prediction of future screening results.

Geir Severin R. E. Langberg, Mikal Stapnes, Jan F. Nygård, Mari Nygård, Markus Grasmair, Valeriya Naumova

BMC Bioinform., 2022

2021

Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective.

Vinay Chakravarthi Gogineni, Severin R. E. Langberg, Valeriya Naumova, Jan F. Nygård, Mari Nygård, Markus Grasmair, Stefan Werner

Proceedings of the IEEE Statistical Signal Processing Workshop, 2021

Recurrent Time-Varying Multi-Graph Convolutional Neural Network for Personalized Cervical Cancer Risk Prediction.

Vinay Chakravarthi Gogineni, Severin R. E. Langberg, Valeriya Naumova, Jan F. Nygård, Mari Nygård, Markus Grasmair, Stefan Werner

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Subgradient-based Lavrentiev regularisation of monotone ill-posed problems.

Markus Grasmair, Fredrik Hildrum

CoRR, 2020

Source Conditions for non-quadratic Tikhonov Regularisation.

Markus Grasmair

CoRR, 2020

2017

Adaptive multi-penalty regularization based on a generalized Lasso path.

Markus Grasmair, Timo Klock, Valeriya Naumova

CoRR, 2017

2015

Optical Flow on Moving Manifolds.

Martin Bauer, Markus Grasmair, Clemens Kirisits

SIAM J. Imaging Sci., 2015

Landmark-Guided Elastic Shape Analysis of Human Character Motions.

Martin Bauer, Markus Eslitzbichler, Markus Grasmair

CoRR, 2015

2013

Scale and Edge Detection with Topological Derivatives.

Guozhi Dong, Markus Grasmair, Sung Ha Kang, Otmar Scherzer

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2013

2012

Shape Reconstruction with A Priori Knowledge Based on Integral Invariants.

Thomas Fidler, Markus Grasmair, Otmar Scherzer

SIAM J. Imaging Sci., 2012

2011

The residual method for regularizing ill-posed problems.

Markus Grasmair, Markus Haltmeier, Otmar Scherzer

Appl. Math. Comput., 2011

2009

Locally Adaptive Total Variation Regularization.

Markus Grasmair

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2009

Variational Methods in Imaging.

Otmar Scherzer, Markus Grasmair, Harald Grossauer, Markus Haltmeier, Frank Lenzen

Applied mathematical sciences 167, Springer, ISBN: 978-0-387-30931-6, 2009

2007

The Equivalence of the Taut String Algorithm and BV-Regularization.

Markus Grasmair

J. Math. Imaging Vis., 2007

2005

A Non-convex PDE Scale Space.

Markus Grasmair, Frank Lenzen, Andreas Obereder, Otmar Scherzer, Matthias Fuchs

Proceedings of the Scale Space and PDE Methods in Computer Vision, 2005