Latent causal DAGs and variables are fully recoverable up to minor indeterminacies from general environments under nonparametric mixing by leveraging sufficient changes in causal mechanisms up to third-order derivatives.
Proof.Let (ˆg, p ˆZ,G ˆZ) be an output of Line 3 in Algorithm 1 during the (n−1)-th iteration, which corresponds to the output of Algorithm 1
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Causal Representation Learning from General Environments under Nonparametric Mixing
Latent causal DAGs and variables are fully recoverable up to minor indeterminacies from general environments under nonparametric mixing by leveraging sufficient changes in causal mechanisms up to third-order derivatives.