An Institution for Simple UML State Machines. - Alexander Knapp; Till Mossakowski; Markus Roggenbach; Martin Glauer (FASE, 2015)

Towards Online Detection of Neural Assemblies in Parallel Spike Trains. - Christian Braune; Martin Glauer; Rudolf Kruse (HICSS, 2015)

Institutions for SQL Database Schemas and Datasets. - Martin Glauer; Till Mossakowski (WADT, 2018)

Towards Fuzzy Neural Conceptors. - Till Mossakowski; Razvan Diaconescu; Martin Glauer (FLAP, 2019)

Automated and Explainable Ontology Extension based on Deep Learning: A Case Study in the Chemical Domain. - Adel Memariani; Martin Glauer; Fabian Neuhaus; Till Mossakowski; Janna Hastings (DAO-XAI, 2021)

FOWL - An OWL to FOL Translator. - Simon Flügel; Anna Kleinau; Fabian Neuhaus; Martin Glauer; Janna Hastings (JOWO, 2021)

Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification. - Janna Hastings; Martin Glauer; Adel Memariani; Fabian Neuhaus; Till Mossakowski (J. Cheminformatics, 2021)

ESC-Rules: Explainable, Semantically Constrained Rule Sets. - Martin Glauer; Robert West; Susan Michie; Janna Hastings (NeSy, 2022)

When one Logic is Not Enough: Integrating First-order Annotations in OWL Ontologies. - Simon Flügel; Martin Glauer; Fabian Neuhaus; Janna Hastings (CoRR, 2022)

Ontology Pre-training for Poison Prediction. - Martin Glauer; Fabian Neuhaus; Till Mossakowski; Janna Hastings (KI, 2023)

Neuro-Symbolic Semantic Learning for Chemistry. - Martin Glauer; Till Mossakowski; Fabian Neuhaus; Adel Memariani; Janna Hastings (Compendium of Neurosymbolic Artificial Intelligence, 2023)

A Fuzzy Loss for Ontology Classification. - Simon Flügel; Martin Glauer; Till Mossakowski; Fabian Neuhaus (NeSy (1), 2024)

A semantic loss for ontology classification. - Simon Flügel; Martin Glauer; Till Mossakowski; Fabian Neuhaus (CoRR, 2024)

Interpretable ontology extension in chemistry. - Martin Glauer; Adel Memariani; Fabian Neuhaus; Till Mossakowski; Janna Hastings (Semantic Web, 2024)

Knowledge and learning: synergies between ontologies and machine learning. - Martin Glauer (2024)

ChemLog: Making MSOL Viable for Ontological Classification and Learning. - Simon Flügel; Martin Glauer; Till Mossakowski; Fabian Neuhaus (CoRR, 2025)