Proposes a lower time-complexity algorithm for identifying distribution-equivalence patterns in linear causal models with Gaussian disturbances via generalized ancestral relationships.
RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders
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Learning linear acyclic causal model including Gaussian noise using ancestral relationships
Proposes a lower time-complexity algorithm for identifying distribution-equivalence patterns in linear causal models with Gaussian disturbances via generalized ancestral relationships.