Biblio
Export 147 results:
Author Title Type [ Year] Filters: First Letter Of Last Name is S [Clear All Filters]
Deep transformation models for functional outcome prediction after acute ischemic stroke.
Biometrical Journal. 65, 2100379.
(2023). Short-term density forecasting of low-voltage load using Bernstein-polynomial normalizing flows.
IEEE Transactions on Smart Grid.
(2023). Deep and interpretable regression models for ordinal outcomes.
Pattern Recognition. 122, 108263.
(2022). Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations.
2021 International Conference on Data Mining Workshops (ICDMW). 398-404.
(2021). Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations.
2021 International Conference on Data Mining Workshops (ICDMW). 398–404.
(2021). Deep transformation models: Tackling complex regression problems with neural network based transformation models.
Accepted for Proceedings of the 25th International Conference on Pattern Recognition (ICPR), Milan/Online, 2021.
(2021). Probabilistic Short-Term Low-Voltage Load Forecasting using Bernstein-Polynomial Normalizing Flows.
ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual. Arpogaus2021_Probabilistic_Forecasting.pdf (427.35 KB)
(2021). Probabilistic short-term low-voltage load forecasting using bernstein-polynomial normalizing flows.
ICML 2021, Workshop Tackling Climate Change with Machine Learning, June 26, 2021, virtual.
(2021). Transformation models for flexible posteriors in variational bayes.
arXiv preprint. 2106.00528. 2106.00528.pdf (1.03 MB)
(2021). Deep and interpretable regression models for ordinal outcomes.
arXiv preprint. 2010.08376.
(2020). Integrating uncertainty in deep neural networks for MRI based stroke analysis.
Medical Image Analysis. 65, 101790.
(2020). Ordinal neural network transformation models: deep and interpretable regression models for ordinal outcomes.
arXiv e-prints. 2010.08376.
(2020).
(2020).
(2020). Single Shot MC Dropout Approximation.
ICML Workshop on Uncertainty and Robustness in Deep Learning.
(2020). Beyond ImageNet: Deep Learning in Industrial Practice.
Applied Data Science. 205-232.
(2019). Beyond ImageNet: Deep Learning in Industrial Practice.
Applied Data Science. 205-232.
(2019).
(2019). Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.
15th IAPR International Conference on Document Analysis and Recognition. Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.pdf (553.24 KB)
(2019). Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.
15th IAPR International Conference on Document Analysis and Recognition. Dissecting Multi-Line Handwriting for Multi-Dimensional Connectionist Classification.pdf (553.24 KB)
(2019). Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.
ICDAR-OST: The 2nd International Workshop on Open Services and Tools for Document Analysis. Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
(2019). Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.
ICDAR-OST: The 2nd International Workshop on Open Services and Tools for Document Analysis. Fast and Reliable Acquisition of Truth Data for Document Analysis using Cyclic Suggest Algorithms.pdf (776.45 KB)
(2019). Automatic classification of non-small cell lung cancer histologic sub-types by deep learning.
VIRCHOWS ARCHIV. 108-108.
(2018). Automatic classification of non-small cell lung cancer histologic sub-types by deep learning.
VIRCHOWS ARCHIV. 108-108.
(2018). Capturing Suprasegmental Features of a Voice with RNNs for Improved Speaker Clustering.
IAPR Workshop on Artificial Neural Networks in Pattern Recognition. 333–345. ANNPR_2018b.pdf (692.47 KB)
(2018).