26 citations · 30 across the 10 of their papers we have counts for
10 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…
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, f…
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…
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…
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…
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…
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…
Lattice-preserving ontology embeddings with saturation
Fernando Zhapa-Camacho, Robert Hoehndorf
Generating vector representations (embeddings) of OWL ontologies is a growing task due to its applications in predicting missing facts and knowledge-enhanced learning in fields suc…
From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddings
Fernando Zhapa-Camacho, Robert Hoehndorf
Several approaches have been developed that generate embeddings for Description Logic ontologies and use these embeddings in machine learning. One approach of generating ontologies…