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eess.SP2026
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…
eess.SP2025
Non-negative DAG Learning from Time-Series Data
Samuel Rey, Gonzalo Mateos
This work aims to learn the directed acyclic graph (DAG) that captures the instantaneous dependencies underlying a multivariate time series. The observed data follow a linear struc…
eess.SP2025
Directed Acyclic Graph Convolutional Networks
Samuel Rey, Hamed Ajorlou, Gonzalo Mateos
Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architecture search. In this work, we introduc…