Leemhuis, M. (2024a). Conceptual Orthospaces — An Embedding Framework Accounting for Negation Operators and Convexity Constraints [Phdthesis]. Institute of Information Systems, University of Lübeck, Germany.

Leemhuis, M. (2024b). Embedding Temporal Description Logic Ontologies by Cone-based Geometric Models. 10th Workshop on Formal and Cognitive Reasoning (FCR-2024) at the 47th German Conference on Artificial Intelligence (KI-2024, September 23 - 27),Würzburg, Germany.

Leemhuis, M., & Kutz, O. (2024). A Cloud Full of Paths: Conceptual Blending as Betweenness Relation. The Eighth Image Schema Day (ISD8), November 27-28, 2024, Bozen-Bolzano, Italy.

Leemhuis, M., Wolter, D., & Özçep, Ö. L. (2024a). Decomposing Analogy: A Logic Characterization. In Foundations of Information and Knowledge Systems (pp. 256–274). Springer Nature Switzerland. DOI

Leemhuis, M., Wolter, D., & Özçep, Ö. L. (2024b). Rules of Partial Orthomodularity. In Logic, Language, Information, and Computation (pp. 108–121). Springer Nature Switzerland. DOI

Maas, J., Leemhuis, M., Mertens, J., Schmidtke, H., Courant, R., Dahlmann, M., Stark, S., Böhm, A., Pagel, K., Hinze, M., Pinkal, D., Wegener, M., Wagner, M. F., Sattel, T., Neubert, H., & Özçep, Ö. (2024). A Novel Digitalization Approach for Smart Materials – Ontology‐Based Access to Data and Models. Advanced Engineering Materials. DOI

Özçep, Ö. L., Leemhuis, M., Winkler, M., Courant, R., Sattel, T., & Maas, J. (2024). Modeling and Accessing Smart Materials with Shapes Constraint Language Integrity Constraints and Ontologies—The SmaDi Way. Advanced Engineering Materials. DOI

Bayerlein, B., Waitelonis, J., Birkholz, H., Jung, M., Schilling, M., v. Hartrott, P., Bruns, M., Schaarschmidt, J., Beilke, K., Mutz, M., Nebel, V., Königer, V., Beran, L., Kraus, T., Vyas, A., Vogt, L., Blum, M., Ell, B., Chen, Y.-F., Waurischk, T., Thomas, A., Durmaz, A. R., Ben Hassine, S., Fresemann, C., Dziwis, G., Nasrabadi, H. B., Hanke, T., Telong, M., Pirskawetz, S., Kamal, M., Bjarsch, T., Pähler, U., Hofmann, P., Leemhuis, M., Özçep, Ö. L., Meyer, L.-P., Skrotzki, B., Neugebauer, J., Wenzel, W., Sack, H., Eberl, C., Dolabella Portella, P., Hickel, T., Mädler, L. & Gumbsch P. (2024). Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science. Advanced Engineering Materials. DOI

Özçep, Ö. L., Leemhuis, M., & Wolter, D. (2023). Embedding Ontologies in the description logic ALC by Axis-Aligned Cones. Journal of Artificial Intelligence Research, 78, 217–267. DOI

Schiff, S., Leemhuis, M., Özçep, Ö. L., & Möller, R. (2023). Query Transformation for Processing Streams in Decision-making Agents. The International FLAIRS Conference Proceedings, 36. DOI

Schmidtke, H. R., Leemhuis, M., Mertens, J., Courant, R., Maas, J., & Özçep, Ö. L. (2023). Bridging the Gap: Intelligent Environments with Smart Materials. 2023 19th International Conference on Intelligent Environments (IE), 1–8. DOI

Mertens, J., Leemhuis, M., Schmidtke, H. R., Özçep, Ö. L., & Maas, J. (2023). Digitalized data access of DE material models and their parameters using an OBD(M)A approach. In J. D. Madden, I. A. Anderson, & H. R. Shea (Eds.), Electroactive Polymer Actuators and Devices (EAPAD) XXV. SPIE. DOI

Leemhuis, M., & Özçep, Ö. L. (2023a). Conceptual Orthospaces—Convexity Meets Negation. International Journal of Approximate Reasoning, 162, 109013. DOI

Leemhuis, M., & Özçep, Ö. L. (2023b). Analogical Proportions and Betweenness. Proceedings of the 9th Workshop on Formal and Cognitive Reasoning, Co-Located with the 46th German Conference on Artificial Intelligence (KI 2023), 8–19.

Leemhuis, M., & Özçep, Ö. L. (2022). A Goodman-style Betweenness Relation on Orthoframes. In C. Beierle, M. Ragni, K. Sauerwald, F. Stolzenburg, & M. Thimm (Eds.), Proceedings of the 8th Workshop on Formal and Cognitive Reasoning, co-located with the 45th German Conference on Artificial Intelligence (KI 2022).

Leemhuis, M., Özçep, Ö. L., & Wolter, D. (2022a). Learning with cone-based geometric models and orthologics. Annals of Mathematics and Artificial Intelligence, 90, 1–37. DOI

Leemhuis, M., Özçep, Ö. L., & Wolter, D. (2022b). Knowledge Graph Embeddings with Ontologies: Reification for Representing Arbitrary Relations. In R. Bergmann, L. Malburg, S. C. Rodermund, & I. J. Timm (Eds.), German Conference on Artificial Intelligence (Künstliche Intelligenz) (Issue 13404, pp. 146–159). Springer International Publishing. DOI

Leemhuis, M., Özçep, Ö. L., & Wolter, D. (2020b). Multi-label Learning with a Cone-Based Geometric Model. Proceedings of the 25th International Conference on Conceptual Structures (ICCS 2020), 177–185. DOI

Özçep, Ö. L., Leemhuis, M., & Wolter, D. (2020a). Cone Semantics for Logics with Negation. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, 1820–1826. DOI

Özçep, Ö. L., Leemhuis, M., & Wolter, D. (2020b). Cones, Negation, And All That. In U. Schmid, F. Klügl, & D. Wolter (Eds.), Proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020 (Vol. 12325, pp. 235–239). Springer International Publishing.DOI