Biblio
Crowd Management in der Lehre.
Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 123-132.
(2022). DeepDoubt - Improving uncertainty measures in machine learning to improve explainability and transparency.
2022 All-Hands-Meeting of the BMBF-funded AI Research Projects at Munich Center for Machine Learning.
AHM2022_DeepDoubt.pdf (238.98 KB)
(2022). 
Fast and efficient image novelty detection based on mean-shifts.
Sensors | Unusual Behavior Detection Based on Machine Learning .
(2022). Fast and memory-efficient independent component analysis using Lie group techniques.
International Conference on Curves and Surfaces.
(2022). Image novelty detection based on mean-shift and typical set size.
21th International Conference on Image Analysis and Processing, ICIAP.
ICIAP-mean-shift-novelty-detection-preprint.pdf (2.96 MB)
(2022). 
Large-scale independent component analysis by speeding up Lie group techniques.
International Conference on Acoustics, Speech, and Signal Processing, ICASSP.
conference_101719.pdf (646.58 KB)
(2022). 
Mathematik mit digitalen Bildern sichtbar machen.
Seamless Learning, Grenz- und kontextübergreifendes Lehren und Lernen in der Bodenseeregion. 133-145.
(2022). Targetless Lidar-camera registration using patch-wise mutual information.
International Conference on Information Fusion.
mir_reg_patch.pdf (9.58 MB)
(2022). 
Accelerating Active Learning Image Labeling Through Bulk Shift Recommendations.
2021 International Conference on Data Mining Workshops (ICDMW). 398-404.
(2021). Biologically-inspired vs. CNN texture representations in novelty detection.
Applications of Machine Learning 2021. 118430I.
Spie2021.pdf (5.33 MB)
(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). 
Transformation models for flexible posteriors in variational bayes.
arXiv preprint. 2106.00528.
2106.00528.pdf (1.03 MB)
(2021). 
CNN-Based Monocular 3D Ship Detection Using Inverse Perspective.
Global Oceans.
(2020). Damage Detection for Port Infrastructure by Means of Machine-Learning-Algorithms.
FIG Working Week 2020.
Fig2020.pdf (876.57 KB)
(2020). 
Deep and interpretable regression models for ordinal outcomes.
arXiv preprint. 2010.08376.
(2020). Detecting and mapping tree seedlings in UAV imagery using convolutional neural networks and field-verified data.
ISPRS Journal of Photogrammetry and Remote Sensing. 168, 156 - 169.
(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). 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).
(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). 