12 citations · 17 across the 5 of their papers we have counts for
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cs.LG2021
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach
Johannes Rabold, Michael Siebers, Ute Schmid
In recent research, human-understandable explanations of machine learning models have received a lot of attention. Often explanations are given in form of model simplifications or…
cs.LG2021★ 12 cited
Expressive Explanations of DNNs by Combining Concept Analysis with ILP
Johannes Rabold, Gesina Schwalbe, Ute Schmid
Explainable AI has emerged to be a key component for black-box machine learning approaches in domains with a high demand for reliability or transparency. Examples are medical assis…