Hanno Gottschalk
Cited by
Cited by
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
Models of local relativistic quantum fields with indefinite metric (in all dimensions)
S Albeverio, H Gottschalk, JL Wu
Communications in mathematical physics 184 (3), 509-531, 1997
A probabilistic model for LCF
S Schmitz, T Seibel, T Beck, G Rollmann, R Krause, H Gottschalk
Computational Materials Science 79, 584-590, 2013
Scattering Theory for Quantum Fields¶ with Indefinite Metric
S Albeverio, H Gottschalk
Communications in Mathematical Physics 216 (3), 491-513, 2001
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
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
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
Dynamical backreaction in Robertson–Walker spacetime
B Eltzner, H Gottschalk
Reviews in Mathematical Physics 23 (05), 531-551, 2011
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
ASME Turbo Expo 2017: Turbomachinery Technical Conference and Exposition, 2017
The Feynman graph representation of convolution semigroups and its applications to Lévy statistics
H Gottschalk, B Smii, H Thaler
Bernoulli 14 (2), 322-351, 2008
Nontrivial scattering amplitudes for some local relativistic quantum field models with indefinite metric
S Albeverio, H Gottschalk, JL Wu
Physics Letters B 405 (3-4), 243-248, 1997
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
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
Feynman graph representation of the perturbation series for general functional measures
SH Djah, H Gottschalk, H Ouerdiane
Journal of functional Analysis 227 (1), 153-187, 2005
Minimal failure probability for ceramic design via shape control
M Bolten, H Gottschalk, S Schmitz
Journal of Optimization Theory and Applications 166 (3), 983-1001, 2015
Optimal reliability in design for fatigue life
H Gottschalk, S Schmitz
SIAM Journal on Control and Optimization 52 (5), 2727-2752, 2014
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
How to determine the law of the solution to a SPDE driven by a Lévy space-time noise
H Gottschalk, B Smii
J. Math. Phys 43, 1-22, 2007
Scattering behaviour of quantum vector fields obtained from Euclidean covariant SPDEs
S Albeverio, H Gottschalk, JL Wu
Reports on Mathematical Physics 44 (1-2), 21-28, 1999
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
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