66 citations · 66 across the 1 of their papers we have counts for
2 papers
stat.ML2020
Deep and interpretable regression models for ordinal outcomes
Lucas Kook, Lisa Herzog, Torsten Hothorn +2
Outcomes with a natural order commonly occur in prediction tasks and often the available input data are a mixture of complex data like images and tabular predictors. Deep Learning…
eess.IV2020★ 66 cited
Integrating uncertainty in deep neural networks for MRI based stroke analysis
Lisa Herzog, Elvis Murina, Oliver Dürr +2
At present, the majority of the proposed Deep Learning (DL) methods provide point predictions without quantifying the models uncertainty. However, a quantification of the reliabili…