This paper studies the feasibility and interpretation of learning the causal structure from observational data with the principles behind the Kolmogorov Minimal Sufficient Statist...
Working within the decision-theoretic framework for causal inference, we study the properties of "sufficient covariates", which support causal inference from observation...
Directed acyclic graph (DAG) models are popular tools for describing causal relationships and for guiding attempts to learn them from data. In particular, they appear to supply a ...
Heckerman (1993) defined causal independence in terms of a set of temporal conditional independence statements. These statements formalized certain types of causal interaction whe...