Biblio
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Author Title Type [ Year] Filters: First Letter Of Last Name is K [Clear All Filters]
Deep transformation models for functional outcome prediction after acute ischemic stroke.
Biometrical Journal. 65, 2100379.
(2023). Extended Target Tracking With a Lidar Sensor Using Random Matrices and a Gaussian Processes Regression Model.
International Conference on Information Fusion (FUSION). 1-8.
(2023). Deep and interpretable regression models for ordinal outcomes.
Pattern Recognition. 122, 108263.
(2022). 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). Ordinal neural network transformation models: deep and interpretable regression models for ordinal outcomes.
arXiv e-prints. 2010.08376.
(2020). Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.
Visualization in Data Science (VDS at IEEE VIS) 2018. Visualization-Assisted Development of Deep Learning Models in Offline Handwriting Recognition.pdf (1.03 MB)
(2018). Analyzing environmental conditions and vital signs to increase healthy living.
Mobile Networks for Biometric Data Analysis.
(2016). Natural neighbor interpolation and order of continuity.
(Hagen, H., Kerren A., & Dannenmann P., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. NatNeighborInterp.pdf (1.47 MB)
(2006). Topographic distance functions for interpolation of meteorological data.
(Hagen, H., Kerren A., & Dannenmann P., Ed.).GI Lecture Notes in Informatics, Visualization of Large and Unstructured Data Sets. TopoDistFunc.pdf (2.27 MB)
(2006).