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Manuel Haussmann
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Deep-learning jets with uncertainties and more
S Bollweg, M Haussmann, G Kasieczka, M Luchmann, T Plehn, ...
SciPost Physics 8 (1), 006, 2020
372020
Deep Active Learning with Adaptive Acquisition
M Haußmann, FA Hamprecht, M Kandemir
International Joint Conference on Artificial Intelligence (IJCAI), arXiv …, 2019
232019
Variational Bayesian Multiple Instance Learning with Gaussian Processes
M Haußmann, FA Hamprecht, M Kandemir
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 6570-6579, 2017
212017
Sampling-free variational inference of bayesian neural networks by variance backpropagation
M Haußmann, FA Hamprecht, M Kandemir
Uncertainty in Artificial Intelligence, 563-573, 2020
18*2020
Understanding Event-Generation Networks via Uncertainties
M Bellagente, M Haußmann, M Luchmann, T Plehn
arXiv preprint arXiv:2104.04543, 2021
172021
LeMoNADe: learned motif and neuronal assembly detection in calcium imaging videos
E Kirschbaum, M Haußmann, S Wolf, H Sonntag, J Schneider, S Elzoheiry, ...
International Conference on Learning Representations 2019, arXiv preprint …, 2018
82018
Variational Weakly Supervised Gaussian Processes.
M Kandemir, M Haußmann, F Diego, KT Rajamani, J Van Der Laak, ...
BMVC, 71.1-71.12, 2016
82016
Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes
M Haußmann, S Gerwinn, A Look, B Rakitsch, M Kandemir
International Conference on Artificial Intelligence and Statistics, 478-486, 2021
62021
Bayesian Evidential Deep Learning with PAC Regularization
M Haussmann, S Gerwinn, M Kandemir
3rd Advances in Approximate Bayesian Inference (AABI) Symposium, arXiv …, 2019
4*2019
Evidential Turing Processes
M Kandemir, A Akgül, M Haussmann, G Unal
arXiv preprint arXiv:2106.01216, 2021
12021
Control and monitoring of physical system based on trained Bayesian neural network
M Kandemir, M Haussmann
US Patent 11,275,381, 2022
2022
Bayesian Neural Networks for Probabilistic Machine Learning
M Haußmann
2021
Supplementary Material for the Paper:” Variational Bayesian Multiple Instance Learning with Gaussian Processes”
M Haußmann, FA Hamprecht, M Kandemir
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Articles 1–13