Topological Conditional Separation

Abstract

Pearl's d-separation is a foundational notion to study conditional independence between random variables. We define the topological conditional separation and we show that it is equivalent to the d-separation, extended beyond acyclic graphs, be they finite or infinite.

References in corpus (1)

• Causal Inference Theory with Information Dependency Models

Cited by in corpus (1)

• Causal Inference Theory with Information Dependency Models