601 citations · 1.3k across the 28 of their papers we have counts for
13 papers · 1 filter
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…
Causal knowledge graph analysis identifies adverse drug effects
Sumyyah Toonsi, Paul Schofield, Robert Hoehndorf
Knowledge graphs and structural causal models have each proven valuable for organizing biomedical knowledge and estimating causal effects, but remain largely disconnected: knowledg…
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…
Towards Automated Functional Equation Proving: A Benchmark Dataset and A Domain-Specific In-Context Agent
Mahdi Buali, Robert Hoehndorf
Automated Theorem Proving (ATP) faces challenges due to its complexity and computational demands. Recent work has explored using Large Language Models (LLMs) for ATP action selecti…
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…
An Open-Source Knowledge Graph Ecosystem for the Life Sciences
Tiffany J. Callahan, Ignacio J. Tripodi, Adrianne L. Stefanski +29
Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these…
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…
FALCON: Scalable Reasoning over Inconsistent ALC Ontologies
Tilman Hinnerichs, Zhenwei Tang, Xi Peng +2
Ontologies are one of the richest sources of knowledge. Real-world ontologies often contain thousands of axioms and are often human-made. Hence, they may contain inconsistency and…
TAR: Neural Logical Reasoning across TBox and ABox
Zhenwei Tang, Shichao Pei, Xi Peng +3
Many ontologies, i.e., Description Logic (DL) knowledge bases, have been developed to provide rich knowledge about various domains. An ontology consists of an ABox, i.e., assertion…
Description Logic EL++ Embeddings with Intersectional Closure
Xi Peng, Zhenwei Tang, Maxat Kulmanov +2
Many ontologies, in particular in the biomedical domain, are based on the Description Logic EL++. Several efforts have been made to interpret and exploit EL++ ontologies by distrib…
EL Embeddings: Geometric construction of models for the Description Logic EL ++
Maxat Kulmanov, Wang Liu-Wei, Yuan Yan +1
An embedding is a function that maps entities from one algebraic structure into another while preserving certain characteristics. Embeddings are being used successfully for mapping…
Towards quantitative measures in applied ontology
Robert Hoehndorf, Michel Dumontier, Georgios V. Gkoutos
Applied ontology is a relatively new field which aims to apply theories and methods from diverse disciplines such as philosophy, cognitive science, linguistics and formal logics to…