AI RESEARCH
Causal Discovery via Quantile Partial Effect
arXiv CS.LG
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ArXi:2509.12981v2 Announce Type: replace Quantile Partial Effect (QPE) is a statistic associated with conditional quantile regression, measuring the effect of covariates at different levels. Our theory nstrates that when the QPE of cause on effect is assumed to lie in a finite linear span, cause and effect are identifiable from their observational distribution. This generalizes previous identifiability results based on Functional Causal Models (FCMs) with additive, heteroscedastic noise, etc.