4 papers
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…
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…
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…
Large-Scale Knowledge Integration for Enhanced Molecular Property Prediction
Yasir Ghunaim, Robert Hoehndorf
Pre-training machine learning models on molecular properties has proven effective for generating robust and generalizable representations, which is critical for advancements in dru…