24 citations · 28 across the 2 of their papers we have counts for
4 papers
Calibrated simplex-mapping classification
Raoul Heese, Jochen Schmid, Michał Walczak +1
We propose a novel methodology for general multi-class classification in arbitrary feature spaces, which results in a potentially well-calibrated classifier. Calibrated classifiers…
The Good, the Bad and the Ugly: Augmenting a black-box model with expert knowledge
Raoul Heese, Michał Walczak, Lukas Morand +2
We address a non-unique parameter fitting problem in the context of material science. In particular, we propose to resolve ambiguities in parameter space by augmenting a black-box…
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems
Laura von Rueden, Sebastian Mayer, Katharina Beckh +11
Despite its great success, machine learning can have its limits when dealing with insufficient training data. A potential solution is the additional integration of prior knowledge…
Optimized data exploration applied to the simulation of a chemical process
Raoul Heese, Michal Walczak, Tobias Seidel +2
In complex simulation environments, certain parameter space regions may result in non-convergent or unphysical outcomes. All parameters can therefore be labeled with a binary class…