3 papers
cs.LG2026
Explaining k-Nearest Neighbors: Abductive and Counterfactual Explanations
Pablo Barceló, Alexander Kozachinskiy, Miguel Romero Orth +2
Despite the wide use of -Nearest Neighbors as classification models, their explainability properties remain poorly understood from a theoretical perspective. While nearest neigh…
cs.LG2025
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barceló, Michael M. Bronstein +4
Knowledge Graph Foundation Models (KGFMs) are at the frontier for deep learning on knowledge graphs (KGs), as they can generalize to completely novel knowledge graphs with differen…
cs.LG2025
Link Prediction with Relational Hypergraphs
Xingyue Huang, Miguel Romero Orth, Pablo Barceló +2
Link prediction with knowledge graphs has been thoroughly studied in graph machine learning, leading to a rich landscape of graph neural network architectures with successful appli…