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Matthias Rottmann
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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
1362014
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
532016
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
382018
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
362020
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
312016
Adaptive algebraic multigrid on SIMD architectures
S Heybrock, M Rottmann, P Georg, T Wettig
arXiv preprint arXiv:1512.04506, 2015
312015
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
29*2019
Inspect, understand, overcome: a survey of practical methods for AI safety
S Houben, S Abrecht, M Akila, A Bär, F Brockherde, P Feifel, ...
Deep Neural Networks and Data for Automated Driving, 3-78, 2022
232022
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/CVF Conference on Computer Vision and Pattern …, 2019
232019
Time-dynamic estimates of the reliability of deep semantic segmentation networks
K Maag, M Rottmann, H Gottschalk
2020 IEEE 32nd International Conference on Tools with Artificial …, 2020
222020
Deep bayesian active semi-supervised learning
M Rottmann, K Kahl, H Gottschalk
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
222018
Detection and retrieval of out-of-distribution objects in semantic segmentation
P Oberdiek, M Rottmann, GA Fink
Proceedings of the ieee/cvf conference on computer vision and pattern …, 2020
172020
Entropy maximization and meta classification for out-of-distribution detection in semantic segmentation
R Chan, M Rottmann, H Gottschalk
Proceedings of the ieee/cvf international conference on computer vision …, 2021
162021
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
152013
Segmentmeifyoucan: A benchmark for anomaly segmentation
R Chan, K Lis, S Uhlemeyer, H Blum, S Honari, R Siegwart, M Salzmann, ...
arXiv preprint arXiv:2104.14812, 2021
142021
MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection
M Schubert, K Kahl, M Rottmann
arXiv preprint arXiv:2010.01695, 2020
132020
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
13*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
102020
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/CVF Conference on Computer Vision and Pattern …, 2019
92019
Aggregation-based Multilevel Methods for Lattice QCD
M Rottmann, A Frommer, K Kahl, S Krieg, B Leder
Proceedings of the XXIX International Symposium on Lattice Field Theory …, 2011
9*2011
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