2 papers
cs.LG2026
Learning Sparsest Linear Causal DAGs with Latent Confounders via Higher-Order Cumulants
Ming Cai, Hisayuki Hara
Recovering the exact directed acyclic graph (DAG) in linear non-Gaussian acyclic models with latent confounders (LvLiNGAM) remains a challenging problem. Although LvLiNGAM is ident…
cs.LG2025
Causal Discovery for Linear DAGs with Dependent Latent Variables via Higher-order Cumulants
Ming Cai, Penggang Gao, Hisayuki Hara
This paper addresses the problem of estimating causal directed acyclic graphs in linear non-Gaussian acyclic models with latent confounders (LvLiNGAM). Existing methods assume mutu…