activity
20242026
collaborators

8 papers

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.AI2026

Fully Geometric Multi-Hop Reasoning on Knowledge Graphs with Transitive Relations

Fernando Zhapa-Camacho, Robert Hoehndorf

Multi-hop logical reasoning on knowledge graphs requires faithfully mapping the logical semantics to latent space. Current geometric embedding methods show to be useful on this tas…

cs.AI2026

A homotopy-type-theoretic generalization of neurosymbolic inference

Fernando Zhapa-Camacho, Robert Hoehndorf

A wide range of neurosymbolic (NeSy) systems compute one functional: a belief-weighted sum of a logical quantity over a space of -structures, of which weighted model counting,…

q-bio.QM2026

INDIGENA: inductive prediction of disease-gene associations using phenotype ontologies

Fernando Zhapa-Camacho, Robert Hoehndorf

Motivation: Predicting gene-disease associations (GDAs) is the problem to determine which gene is associated with a disease. GDA prediction can be framed as a ranking problem where…

cs.AI2025

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.AI2025

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…