Matthias Rottmann
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Zitiert von
Jahr
Adaptive aggregation-based domain decomposition multigrid for the lattice Wilson--Dirac operator
A Frommer, K Kahl, S Krieg, B Leder, M Rottmann
SIAM journal on scientific computing 36 (4), A1581-A1608, 2014
962014
Adaptive aggregation-based domain decomposition multigrid for twisted mass fermions
C Alexandrou, S Bacchio, J Finkenrath, A Frommer, K Kahl, M Rottmann
Physical Review D 94 (11), 114509, 2016
362016
Multigrid preconditioning for the overlap operator in lattice QCD
J Brannick, A Frommer, K Kahl, B Leder, M Rottmann, A Strebel
Numerische Mathematik 132 (3), 463-490, 2016
262016
Application of decision rules for handling class imbalance in semantic segmentation
R Chan, M Rottmann, F Hüger, P Schlicht, H Gottschalk
arXiv preprint arXiv:1901.08394, 2019
16*2019
Classification uncertainty of deep neural networks based on gradient information
P Oberdiek, M Rottmann, H Gottschalk
IAPR Workshop on Artificial Neural Networks in Pattern Recognition, 113-125, 2018
162018
Adaptive algebraic multigrid on SIMD architectures
S Heybrock, M Rottmann, P Georg, T Wettig
arXiv preprint arXiv:1512.04506, 2015
162015
Prediction error meta classification in semantic segmentation: Detection via aggregated dispersion measures of softmax probabilities
M Rottmann, P Colling, TP Hack, R Chan, F Hüger, P Schlicht, ...
2020 International Joint Conference on Neural Networks (IJCNN), 1-9, 2020
132020
Uncertainty measures and prediction quality rating for the semantic segmentation of nested multi resolution street scene images
M Rottmann, M Schubert
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
102019
An adaptive aggregation based domain decomposition multilevel method for the lattice Wilson Dirac operator: multilevel results
A Frommer, K Kahl, S Krieg, B Leder, M Rottmann
arXiv preprint arXiv:1307.6101, 2013
102013
Time-dynamic estimates of the reliability of deep semantic segmentation networks
K Maag, M Rottmann, H Gottschalk
arXiv preprint arXiv:1911.05075, 2019
82019
Deep bayesian active semi-supervised learning
M Rottmann, K Kahl, H Gottschalk
arXiv preprint arXiv:1803.01216, 2018
8*2018
Aggregation-based Multilevel Methods for Lattice QCD
M Rottmann, A Frommer, K Kahl, S Krieg, B Leder
XXIX International Symposium on Lattice Field Theory 139, 046, 2012
8*2012
Adaptive domain decomposition multigrid for lattice QCD
M Rottmann
Universität Wuppertal, Fakultät für Mathematik und Naturwissenschaften …, 2018
62018
The ethical dilemma when (not) setting up cost-based decision rules in semantic segmentation
R Chan, M Rottmann, R Dardashti, F Huger, P Schlicht, H Gottschalk
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019
52019
Least angle regression coarsening in bootstrap algebraic multigrid
K Kahl, M Rottmann
SIAM Journal on Scientific Computing 40 (6), A3928-A3954, 2018
42018
DDalphaAMG for twisted mass fermions
S Bacchio, C Alexandrou, J Finkenrath, A Frommer, K Kahl, M Rottmann
arXiv preprint arXiv:1611.01034, 2016
42016
Controlled False Negative Reduction of Minority Classes in Semantic Segmentation
R Chan, M Rottmann, F Hüger, P Schlicht, H Gottschalk
2020 International Joint Conference on Neural Networks (IJCNN), 1-8, 2020
2*2020
YOdar: Uncertainty-based Sensor Fusion for Vehicle Detection with Camera and Radar Sensors
K Kowol, M Rottmann, S Bracke, H Gottschalk
arXiv preprint arXiv:2010.03320, 2020
2020
MetaBox+: A new Region Based Active Learning Method for Semantic Segmentation using Priority Maps
P Colling, L Roese-Koerner, H Gottschalk, M Rottmann
arXiv preprint arXiv:2010.01884, 2020
2020
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection
M Schubert, K Kahl, M Rottmann
arXiv preprint arXiv:2010.01695, 2020
2020
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