Ontology-Based Skill Description Learning for Flexible Production Systems. - Anna Himmelhuber; Stephan Grimm; Thomas A. Runkler; Sonja Zillner (ETFA, 2020)

A New Concept for Explaining Graph Neural Networks. - Anna Himmelhuber; Sonja Zillner; Stephan Grimm; Martin Ringsquandl; Mitchell Joblin; Thomas A. Runkler (NeSy, 2021)

Demystifying Graph Neural Network Explanations. - Anna Himmelhuber; Mitchell Joblin; Martin Ringsquandl; Thomas A. Runkler (PKDD/ECML Workshops (1), 2021)

Combining Sub-symbolic and Symbolic Methods for Explainability. - Anna Himmelhuber; Stephan Grimm; Sonja Zillner; Mitchell Joblin; Martin Ringsquandl; Thomas A. Runkler (RuleML+RR, 2021)

Rapid Explainability for Skill Description Learning. - Caglar Demir; Anna Himmelhuber; Yushan Liu 002; Alexander Bigerl; Diego Moussallem; Axel-Cyrille Ngonga Ngomo (ISWC (Posters/Demos/Industry), 2022)

Detection, Explanation and Filtering of Cyber Attacks Combining Symbolic and Sub-Symbolic Methods. - Anna Himmelhuber; Dominik Dold; Stephan Grimm; Sonja Zillner; Thomas A. Runkler (SSCI, 2022)

Combining Sub-Symbolic and Symbolic Methods for Explainability. - Anna Himmelhuber; Stephan Grimm; Mitchell Joblin; Sonja Zillner; Thomas A. Runkler (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Combining Symbolic and Sub-symbolic Methods for explaining Graph Neural Networks. - Anna Himmelhuber (2024)