3 citations · 3 across the 4 of their papers we have counts for
6 papers
Embedding Knowledge Graph in Function Spaces
Louis Mozart Kamdem Teyou, Caglar Demir, Axel-Cyrille Ngonga Ngomo
We introduce a novel embedding method diverging from conventional approaches by operating within function spaces of finite dimension rather than finite vector space, thus departing…
Kronecker Decomposition for Knowledge Graph Embeddings
Caglar Demir, Julian Lienen, Axel-Cyrille Ngonga Ngomo
Knowledge graph embedding research has mainly focused on learning continuous representations of entities and relations tailored towards the link prediction problem. Recent results…
DRILL-- Deep Reinforcement Learning for Refinement Operators in
Caglar Demir, Axel-Cyrille Ngonga Ngomo
Approaches based on refinement operators have been successfully applied to class expression learning on RDF knowledge graphs. These approaches often need to explore a large number…
Out-of-Vocabulary Entities in Link Prediction
Caglar Demir, Axel-Cyrille Ngonga Ngomo
Knowledge graph embedding techniques are key to making knowledge graphs amenable to the plethora of machine learning approaches based on vector representations. Link prediction is…
MLCheck- Property-Driven Testing of Machine Learning Models
Arnab Sharma, Caglar Demir, Axel-Cyrille Ngonga Ngomo +1
In recent years, we observe an increasing amount of software with machine learning components being deployed. This poses the question of quality assurance for such components: how…
A shallow neural model for relation prediction
Caglar Demir, Diego Moussallem, Axel-Cyrille Ngonga Ngomo
Knowledge graph completion refers to predicting missing triples. Most approaches achieve this goal by predicting entities, given an entity and a relation. We predict missing triple…