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cs.LG2026
Exploiting Non-Negativity in DAG Structure Learning
Samuel Rey, Madeline navarro, Gonzalo Mateos +1
This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations adhering to a linear structural equation model. DAG structure learning is a centr…
cs.LG2025
BUILD with Precision: Bottom-Up Inference of Linear DAGs
Hamed Ajorlou, Samuel Rey, Gonzalo Mateos +2
Learning the structure of directed acyclic graphs (DAGs) from observational data is a central problem in causal discovery, statistical signal processing, and machine learning. Unde…