Local Causal Discovery with Linear non-Gaussian Cyclic Models

arXiv:2403.14843v1 Announce Type: new
Abstract: Local causal discovery is of great practical significance, as there are often situations where the discovery of the global causal structure is unnecessary, and the interest lies solely on a single target variable. Most existing local methods utilize conditional independence relations, providing only a partially directed graph, and assume acyclicity for the ground-truth structure, even though real-world scenarios often involve cycles like feedback mechanisms. In this work, we present a general, unified local causal discovery …

abstract arxiv causal cs.ai cs.lg discovery global graph lies linear practical relations significance type