1 citations · 1 across the 7 of their papers we have counts for
3 papers · 1 filter
Nonnegative DAG Learning via Concomitant Estimation
Madeline Navarro, Gonzalo Mateos, Samuel Rey
We study the problem of learning directed acyclic graphs (DAGs) with nonnegative edge weights from observational data. We propose the Nonnegative and Concomitant (NoCo) DAG estimat…
Concomitant DAG Learning: On the Roles of Noise Adaptivity, Sparsity, and Non-negativity
Gonzalo Mateos, Samuel Rey, Hamed Ajorlou +1
Directed acyclic graphs (DAGs) constitute a central modeling tool to enable principled reasoning about cause-effect interactions in complex systems. However, since the causal struc…
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…