Identification of Nonlinear Latent Hierarchical Models Lingjing Kong

Neural Information Processing Systems 

Classical causal structure learning algorithms often assume no latent confounders. However, it is usually impossible to enumerate and measure all task-related variables in real-world scenarios. Neglecting latent confounders may lead to spurious correlations among observed variables.

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