3 papers
cs.AI2026
Unifying Post-hoc Explanations of Knowledge Graph Completions
Alessandro Lonardi, Samy Badreddine, Tarek R. Besold +1
Knowledge Graphs organize information as entity-relation-entity triples, enabling machine learning models to predict plausible missing triples in a task known as Knowledge Graph Co…
cs.AI2026
On the Theoretical Limitations of Embedding-based Link Prediction
Samy Badreddine, Emile van Krieken, Luciano Serafini
Neural networks often map low-dimensional embeddings to high-dimensional output spaces. Usually, the output layer is linear, which can create a "rank bottleneck" that limits the fu…
cs.AI2025
Rewarding Explainability in Drug Repurposing with Knowledge Graphs
Susana Nunes, Samy Badreddine, Catia Pesquita
Knowledge graphs (KGs) are powerful tools for modelling complex, multi-relational data and supporting hypothesis generation, particularly in applications like drug repurposing. How…