Neurosymbolic integration
We develop neurosymbolic integration both at the conceptual level as well as in several application areas, including chemistry, material science and human behaviour. We use well-developed ontological background knowledge in order to enhance the performance of machine learning methods, e.g. by using a semantic loss function or neuro-fuzzy rules. We have developed a novel neurosymbolic architecture for ontological classification of structured entities and of ontology extension.
Current projects
- StrOntEx (Ontology Extension by Automated Learning and Reasoning from Structured Entities) funded by DFG
Completed projects
Publications
2025
Chebifier 2: An Ensemble for Chemistry.
In: S. Tiwari, editor, Symbolic and Generative AI for Science (SymGenAI4Sci 2025). 2025. To appear
Simon Flügel, Martin Glauer, Janna Hastings, Till Mossakowski, Christopher J. Mungall, Charlotte Tumescheit and Fabian Neuhaus.
[BibTeX]
ChemLog: Making MSOL Viable for Ontological Classification and Learning.
In: A. Tamaddoni-Nezhad, editor, 5th International Joint Conference on Learning and Reasoning (IJCLR 2025) . 2025. To appear
Simon Flügel, Martin Glauer, Till Mossakowski and Fabian Neuhaus.
[BibTeX]
Box Embeddings for Extending Ontologies: A Data-Driven and Interpretable Approach.
Journal of Cheminformatics, 17(138), 2025.
Adel Memariani, Martin Glauer, Simon Flügel, Fabian Neuhaus, Janna Hastings and Till Mossakowski.
[doi] [BibTeX]
Monadic ULLER: A Unified Categorical Semantics of the Neurosymbolic ULLER Framework.
In: G. Eleonora, P. Hitzler and E. van Krieken, editors, 19th Conference on Neurosymbolic Learning and Reasoning (NeSy 2025). 2025. to appear
Daniel Schellhorn and Till Mossakowski.
[BibTeX]
Advancing Natural Language formalization to First Order Logic with Fine-tuned LLMs.
In: A. Tamaddoni-Nezhad, editor, 5th International Joint Conference on Learning and Reasoning (IJCLR 2025). 2025. To appear
Felix Vossel, Till Mossakowski and Björn Gehrke.
[BibTeX]
2024
A fuzzy loss for ontology classification.
In: T. R. Besold, A. d'Avila Garcez, E. Jimenez-Ruiz, R. Confalonieri, B. Wagner and P. Madhyastha, editors, NeSy 2024: The 18th International Conference on Neural-symbolic Learning and Reasoning, volume 14979, series Springer lecture notes, pages 101-118. Springer, 2024.
Simon Flügel, Martin Glauer, Till Mossakowski and Fabian Neuhaus.
[abstract] [BibTeX]
Chebifier: Automating semantic classification in ChEBI to accelerate data-driven discovery.
Digital Discovery, 2024.
Martin Glauer, Fabian Neuhaus, Simon Flügel, Marie Wosny, Till Mossakowski, Adel Memariani, Johannes Schwerdt and Janna Hastings.
[doi] [abstract] [BibTeX]
Interpretable Ontology Extension in Chemistry.
Semantic Web journal, 15(4):937-958, 2024. Special Issue on The Role of Ontologies and Knowledge in Explainable AI
Martin Glauer, Adel Memariani, Fabian Neuhaus, Till Mossakowski and Janna Hastings.
[doi] [BibTeX]
2023
Neuro-symbolic semantic learning for chemistry.
In: P. Hitzler, M. K. Sarker and A. Eberhart, editors, A Compendium of Neuro-Symbolic Artificial Intelligence, chapter 21, pages 460 - 484. IOS press, 2023.
Martin Glauer, Till Mossakowski, Fabian Neuhaus, Adel Memariani and Janna Hastings.
[doi] [abstract] [BibTeX]
Ontology Pre-training for Poison Prediction.
In: D. Seipel and A. Steen, editors, German conference on artificial intelligence 2023, volume 14236, series Lecture Notes in Artificial Intelligence, pages 31-45. Springer, 2023. Best paper award. Also available at doi.org/10.48550/arXiv.2301.08577
Martin Glauer, Fabian Neuhaus, Till Mossakowski and Janna Hastings.
[doi] [abstract] [BibTeX]
2022
Modular design patterns for neural-symbolic integration: refinement and combination.
In: A. d'Avila Garcez and E. Jiménez-Ruiz, editors, 16th International Workshop on Neural-Symbolic Learning and Reasoning (NeSy), volume 3212, series CEUR Workshop proceedings, pages 192-201. 2022.
Till Mossakowski.
[doi] [BibTeX]
2021
Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification..
Journal of Cheminformatics, 13(23), 2021.
Janna Hastings, Martin Glauer, Adel Memariani, Fabian Neuhaus and Till Mossakowski.
[doi] [BibTeX]
Automated and explainable ontology extension based on deep learning: A case study in the chemical domain.
In: R. Confalonieri, O. Kutz and D. Calvanese, editors, International Workshop on Data meets Applied Ontologies in Explainable AI (DAO-XAI 2021), volume 2998, series CEUR Workshop Proceedings. ceur-ws.org/Vol-2998/, 2021.
Adel Memariani, Martin Glauer, Fabian Neuhaus, Till Mossakowski and Janna Hastings.
[doi] [BibTeX]
2019
Towards Fuzzy Neural Conceptors.
IfCoLog Journal of Logics and their Applications, 6(4):725-744, 2019.
Till Mossakowski, Razvan Diaconescu and Martin Glauer.
[doi] [BibTeX]