Membership Testing in Markov Equivalence Classes via Independence Query Oracles

arXiv:2403.05759v1 Announce Type: new
Abstract: Understanding causal relationships between variables is a fundamental problem with broad impact in numerous scientific fields. While extensive research has been dedicated to learning causal graphs from data, its complementary concept of testing causal relationships has remained largely unexplored. While learning involves the task of recovering the Markov equivalence class (MEC) of the underlying causal graph from observational data, the testing counterpart addresses the following critical question: Given a specific MEC and observational data from …

abstract arxiv causal concept cs.ai cs.lg data fields graphs impact markov query relationships research stat.me stat.ml testing type understanding variables via