2024
Identification of Causal Structure in the Presence of Missing Data with Additive Noise Model
AAAI 2024technical
Missing data are an unavoidable complication frequently encountered in many causal discovery tasks. When a missing process depends on the missing values themselves (known as self-masking missingness), the recovery of the joint distribution becomes unattainable, and detecting the presence of such se…