244 citations · 964 across the 44 of their papers we have counts for
6 papers · 1 filter
Discovery of non-gaussian linear causal models using ICA
Shohei Shimizu, Aapo Hyvarinen, Yutaka Kano +1
In recent years, several methods have been proposed for the discovery of causal structure from non-experimental data (Spirtes et al. 2000; Pearl 2000). Such methods make various as…
Causal discovery of linear acyclic models with arbitrary distributions
Patrik O. Hoyer, Aapo Hyvarinen, Richard Scheines +4
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used t…
On the Identifiability of the Post-Nonlinear Causal Model
Kun Zhang, Aapo Hyvarinen
By taking into account the nonlinear effect of the cause, the inner noise effect, and the measurement distortion effect in the observed variables, the post-nonlinear (PNL) causal m…
Estimation of causal orders in a linear non-Gaussian acyclic model: a method robust against latent confounders
Tatsuya Tashiro, Shohei Shimizu, Aapo Hyvarinen +1
We consider to learn a causal ordering of variables in a linear non-Gaussian acyclic model called LiNGAM. Several existing methods have been shown to consistently estimate a causal…
Source Separation and Higher-Order Causal Analysis of MEG and EEG
Kun Zhang, Aapo Hyvarinen
Separation of the sources and analysis of their connectivity have been an important topic in EEG/MEG analysis. To solve this problem in an automatic manner, we propose a two-layer…
A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models
Miika Pihlaja, Michael Gutmann, Aapo Hyvarinen
We introduce a new family of estimators for unnormalized statistical models. Our family of estimators is parameterized by two nonlinear functions and uses a single sample from an a…