5 citations · 5 across the 2 of their papers we have counts for
3 papers
cs.LG2026
HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classification
Simon Flügel, Till Mossakowski
While attaining remarkable results for many applications, Deep Learning models are notoriously difficult to explain. This work introduces HyDI, a hybrid ensemble architecture for h…
cs.AI2024
A fuzzy loss for ontology classification
Simon Flügel, Martin Glauer, Till Mossakowski +1
Deep learning models are often unaware of the inherent constraints of the task they are applied to. However, many downstream tasks require logical consistency. For ontology classif…
cs.AI2022★ 5 cited
When one Logic is Not Enough: Integrating First-order Annotations in OWL Ontologies
Simon Flügel, Martin Glauer, Fabian Neuhaus +1
In ontology development, there is a gap between domain ontologies which mostly use the web ontology language, OWL, and foundational ontologies written in first-order logic, FOL. To…