2 citations · 2 across the 2 of their papers we have counts for
3 papers
Approaching Neural Network Uncertainty Realism
Joachim Sicking, Alexander Kister, Matthias Fahrland +5
Statistical models are inherently uncertain. Quantifying or at least upper-bounding their uncertainties is vital for safety-critical systems such as autonomous vehicles. While stan…
Aligning Subjective Ratings in Clinical Decision Making
Annika Pick, Sebastian Ginzel, Stefan Rüping +3
In addition to objective indicators (e.g. laboratory values), clinical data often contain subjective evaluations by experts (e.g. disease severity assessments). While objective ind…
Making Efficient Use of a Domain Expert's Time in Relation Extraction
Linara Adilova, Sven Giesselbach, Stefan Rüping
Scarcity of labeled data is one of the most frequent problems faced in machine learning. This is particularly true in relation extraction in text mining, where large corpora of tex…