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cs.AI2026

Neuro-symbolic learning over OWL 2 DL via consequence-based compilation to differentiable circuits

Olga Mashkova, Asaad Mohammedsaleh, Fernando Zhapa-Camacho +1

OWL 2 DL ontologies, grounded in the description logic , express large knowledge bases in biomedicine and the Semantic Web. Neuro-symbolic (NeSy) learners over des…

cs.AI2026

Moose: Latent concept learning with reasoning-shortcut awareness in

Olga Mashkova, Asaad Mohammedsaleh, Fernando Zhapa-Camacho +1

The OWL 2 EL profile is used in some of the largest production ontologies, including the Gene Ontology and SNOMED CT. Existing neuro-symbolic (NeSy) learning methods accept proposi…

cs.AI2024

DELE: Deductive Embeddings for Knowledge Base Completion

Olga Mashkova, Fernando Zhapa-Camacho, Robert Hoehndorf

Ontology embeddings map classes, roles, and individuals in ontologies into , and within similarity between entities can be computed or new axioms infer…

cs.AI2024

Enhancing Geometric Ontology Embeddings for with Negative Sampling and Deductive Closure Filtering

Olga Mashkova, Fernando Zhapa-Camacho, Robert Hoehndorf

Ontology embeddings map classes, relations, and individuals in ontologies into , and within similarity between entities can be computed or new axioms i…

cs.AI2024

Ontology Embedding: A Survey of Methods, Applications and Resources

Jiaoyan Chen, Olga Mashkova, Fernando Zhapa-Camacho +3

Ontologies are widely used for representing domain knowledge and meta data, playing an increasingly important role in Information Systems, the Semantic Web, Bioinformatics and many…