Hessian Rank Constraint for Learning Structure of Nonlinear Latent Variable Models
A condition called the cross-Hessian Rank Constraint (HRC), which serves as a primitive rank-based tool for nonlinear latent causal discovery, shows that a rank-based property arises from the cross-Hessian of the observed-data log-density in the nonlinear case, revealing information about the latent variables.
Zijian Li, Ruichu Cai, Feng Xie et al.
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