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ParaLiNGAM: Parallel Causal Structure Learning for Linear non-Gaussian Acyclic Models [article]

Amirhossein Shahbazinia, Saber Salehkaleybar, Matin Hashemi
2021 arXiv   pre-print
In linear non-Gaussian acyclic models (LiNGAM), it can be shown that the true underlying causal structure can be identified uniquely from merely observational data.  ...  In this paper, we propose a parallel algorithm, called ParaLiNGAM, to learn casual structures based on DirectLiNGAM algorithm.  ...  They called the non-Gaussian version of the linear acyclic SEM, Linear Non-Gaussian Acyclic Model (LiNGAM).  ... 
arXiv:2109.13993v1 fatcat:7rdxdlrtqvczvd6ombvzzstuse