| 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 | 180 | 2014 |
| 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 | 100 | 2021 |
| Segmentmeifyoucan: A benchmark for anomaly segmentation R Chan, K Lis, S Uhlemeyer, H Blum, S Honari, R Siegwart, M Salzmann, ... NeurIPS 2021 Track Datasets and Benchmarks Round2, 2021 | 95 | 2021 |
| 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 | 82 | 2020 |
| 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 | 79 | 2016 |
| Classification uncertainty of deep neural networks based on gradient information P Oberdiek, M Rottmann, H Gottschalk Artificial Neural Networks in Pattern Recognition: 8th IAPR TC3 Workshop …, 2018 | 66 | 2018 |
| 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: Robustness, Uncertainty …, 2022 | 53 | 2022 |
| Application of maximum likelihood decision rules for handling class imbalance in semantic segmentation RKW Chan, M Rottmann, H Gottschalk, F Hüger, P Schlicht Proceedings of the 30th European Safety and Reliability Conference and 15th …, 2020 | 49* | 2020 |
| 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 | 37 | 2020 |
| 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 | 36 | 2020 |
| 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 | 36 | 2019 |
| 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 | 36 | 2016 |
| Adaptive algebraic multigrid on SIMD architectures S Heybrock, M Rottmann, P Georg, T Wettig arXiv preprint arXiv:1512.04506, 2015 | 35 | 2015 |
| 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 | 33 | 2020 |
| Deep bayesian active semi-supervised learning M Rottmann, K Kahl, H Gottschalk 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 29 | 2018 |
| 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 | 25 | 2020 |
| MetaDetect: Uncertainty Quantification and Prediction Quality Estimates for Object Detection M Schubert, K Kahl, M Rottmann arXiv preprint arXiv:2010.01695, 2020 | 25 | 2020 |
| 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 | 19* | 2020 |
| Detection of false positive and false negative samples in semantic segmentation M Rottmann, K Maag, R Chan, F Hüger, P Schlicht, H Gottschalk 2020 Design, Automation & Test in Europe Conference & Exhibition (DATE …, 2020 | 19 | 2020 |
| 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 | 19 | 2013 |
Hanno GottschalkProfessor for Mathematical Modeling of Industrial Life Cycles, TU BerlinVerified email at math.tu-berlin.de
