Abstract
Directed acyclic graph (DAG) models are popular for capturing causal relationships. From observational and interventional data, a DAG model can only be determined up to its interventional Markov equivalence class (I-MEC). We investigate the size of MECs for random DAG models generated by uniformly sampling and ordering an Erdős-Rényi graph. For constant density, we show that the expected.
Type
Publication
The 22nd Internation Conference on Artificial Intelligence and Statistics
Chandler Squires
Graduate Student
My research interests include causal structure discovery, active learning, and identification of latent variables.