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Hanno Gottschalk
Hanno Gottschalk
Professor for Mathematical Modeling of Industrial Life Cycles, TU Berlin
在 math.tu-berlin.de 的电子邮件经过验证 - 首页
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引用次数
引用次数
年份
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
1102021
Convoluted generalized white noise, Schwinger functions and their analytic continuation to Wightman functions
S Albeverio, H Gottschalk, JL Wu
Reviews in Mathematical Physics 8 (06), 763-817, 1996
991996
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
842020
Combined notch and size effect modeling in a local probabilistic approach for LCF
L Mäde, S Schmitz, H Gottschalk, T Beck
Computational Materials Science 142, 377-388, 2018
812018
A probabilistic model for LCF
S Schmitz, T Seibel, T Beck, G Rollmann, R Krause, H Gottschalk
Computational Materials Science 79, 584-590, 2013
772013
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
672018
Models of local relativistic quantum fields with indefinite metric (in all dimensions)
S Albeverio, H Gottschalk, JL Wu
Communications in mathematical physics 184, 509-531, 1997
651997
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
402019
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
372020
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
372020
Risk estimation for LCF crack initiation
S Schmitz, H Gottschalk, G Rollmann, R Krause
Turbo Expo: Power for Land, Sea, and Air 55263, V07AT27A007, 2013
322013
Probabilistic lcf risk evaluation of a turbine vane by combined size effect and notch support modeling
L Mäde, H Gottschalk, S Schmitz, T Beck, G Rollmann
Turbo Expo: Power for Land, Sea, and Air 50923, V07AT32A004, 2017
312017
Dynamical backreaction in Robertson–Walker spacetime
B Eltzner, H Gottschalk
Reviews in Mathematical Physics 23 (05), 531-551, 2011
312011
Systems of classical particles in the grand canonical ensemble, scaling limits and quantum field theory
S Albeverio, H Gottschalk, MW Yoshida
Reviews in Mathematical Physics 17 (02), 175-226, 2005
312005
Scattering Theory for Quantum Fields¶ with Indefinite Metric
S Albeverio, H Gottschalk
Communications in Mathematical Physics 216, 491-513, 2001
312001
Generative modeling of turbulence
C Drygala, B Winhart, F di Mare, H Gottschalk
Physics of Fluids 34 (3), 2022
292022
Deep bayesian active semi-supervised learning
M Rottmann, K Kahl, H Gottschalk
2018 17th IEEE International Conference on Machine Learning and Applications …, 2018
292018
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
272020
Minimal failure probability for ceramic design via shape control
M Bolten, H Gottschalk, S Schmitz
Journal of Optimization Theory and Applications 166, 983-1001, 2015
252015
Optimal reliability in design for fatigue life
H Gottschalk, S Schmitz
SIAM Journal on Control and Optimization 52 (5), 2727-2752, 2014
252014
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