Network Structure Learning Under Uncertain Interventions

• Published in: Journal of the American Statistical Association Vol. 118; no. 543; pp. 2117 - 2128
• Main Authors: Castelletti, Federico, Peluso, Stefano
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 03.07.2023; Taylor & Francis Ltd
• Subjects: Algorithms; anticonvulsants; Antiepileptic drugs; Bayesian analysis; Bayesian theory; Biology; DAG-Wishart prior; Directed acyclic graph; Graph theory; Graphs; Intervention; Interventional data; Learning; Machine learning; observational studies; Statistics; Target discovery; Uncertainty; Variables

Gaussian Directed Acyclic Graphs (DAGs) represent a powerful tool for learning the network of dependencies among variables, a task which is of primary interest in many fields and specifically in biology. Different DAGs may encode equivalent conditional independence structures, implying limited abili...