14 citations · 16 across the 2 of their papers we have counts for
2 papers
stat.ML2011★ 2 cited
DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model
Shohei Shimizu, Takanori Inazumi, Yasuhiro Sogawa +5
Structural equation models and Bayesian networks have been widely used to analyze causal relations between continuous variables. In such frameworks, linear acyclic models are typic…
cs.AI2006★ 14 cited
Estimation of linear, non-gaussian causal models in the presence of confounding latent variables
Patrik O. Hoyer, Shohei Shimizu, Antti J. Kerminen
The estimation of linear causal models (also known as structural equation models) from data is a well-known problem which has received much attention in the past. Most previous wor…