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Anomaly detection in electrocardiogram readings with stacked LSTM networks
M Thill, S Däubener, W Konen, THW Bäck, P Barancikova, M Holena, ...
Proceedings of the 19th Conference Information Technologies-Applications and …, 2019
262019
Detecting Adversarial Examples for Speech Recognition via Uncertainty Quantification
S Däubener, L Schönherr, A Fischer, D Kolossa
INTERSPEECH, 2020
222020
Anomaly Detection in Univariate Time Series: An Empirical Comparison of Machine Learning Algorithms.
S Däubener, S Schmitt, H Wang, P Krause, T Bäck
ICDM, 161-175, 2019
192019
Predictive uncertainty quantification with compound density networks
A Kristiadi, S Däubener, A Fischer
arXiv preprint arXiv:1902.01080, 2019
152019
Approaches to uncertainty quantification in federated deep learning
F Linsner, L Adilova, S Däubener, M Kamp, A Fischer
Machine Learning and Principles and Practice of Knowledge Discovery in …, 2022
132022
Detecting Compositionally Out-of-Distribution Examples in Semantic Parsing
D Lukovnikov, S Daubener, A Fischer
Findings of the Association for Computational Linguistics: EMNLP 2021, 591-598, 2021
92021
On the Challenges and Opportunities in Generative AI
L Manduchi, K Pandey, R Bamler, R Cotterell, S Däubener, S Fellenz, ...
arXiv preprint arXiv:2403.00025, 2024
52024
How Sampling Impacts the Robustness of Stochastic Neural Networks
S Däubener, A Fischer
arXiv preprint arXiv:2204.10839, 2022
32022
On the Limitations of Model Stealing with Uncertainty Quantification Models
D Pape, S Däubener, T Eisenhofer, AE Cinà, L Schönherr
arXiv preprint arXiv:2305.05293, 2023
22023
SmoothLRP: Smoothing LRP by Averaging over Stochastic Input Variations.
AP Raulf, S Däubener, B Hack, A Mosig, A Fischer
ESANN, 2021
22021
Investigating maximum likelihood based training of infinite mixtures for uncertainty quantification
S Däubener, A Fischer
arXiv preprint arXiv:2008.03209, 2020
22020
Uncertainty quantification with compound density networks
A Kristiadi, S Däubener, A Fischer
Proc. 4th Workshop Bayesian Deep Learn. NeurIPS, 2019
22019
Efficient Calculation of Adversarial Examples for Bayesian Neural Networks
S Däubener, J Frank, T Holz, A Fischer
Third Symposium on Advances in Approximate Bayesian Inference, 0
2*
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