Manuele Leonelli

Structural Learning of Simple Staged Trees

2022 · arXiv (Cornell University)

Bayesian networks faithfully represent the symmetric conditional independences existing between the components of a random vector. Staged trees are an extension of Bayesian networks for categorical random vectors whose graph represents non-symmetric conditional independences via …

Learning and interpreting asymmetry-labeled DAGs: a case study on COVID-19 fear

2023 · arXiv (Cornell University)

Bayesian networks are widely used to learn and reason about the dependence structure of discrete variables. However, they are only capable of formally encoding symmetric conditional independence, which in practice is often too strict to …

Learning Staged Trees from Incomplete Data

2024 · arXiv (Cornell University)

Staged trees are probabilistic graphical models capable of representing any class of non-symmetric independence via a coloring of its vertices. Several structural learning routines have been defined and implemented to learn staged trees from data, …