2026
Identifiability of Causal Graphs under Non-Additive Conditionally Parametric Causal Models
ICML 2026poster
Existing approaches to causal discovery often rely on restrictive modeling assumptions that limit their applicability in real-world settings, particularly when data are heavy-tailed or contain a mixture of discrete and continuous variables. Identifiability of causal graphs has been established under…