Discovery of non-gaussian linear causal models using ICA

@inproceedings{Shimizu2005DiscoveryON,
  title={Discovery of non-gaussian linear causal models using ICA},
  author={Shohei Shimizu and Aapo Hyv{\"a}rinen and Yutaka Kano and Patrik O. Hoyer},
  booktitle={UAI},
  year={2005}
}
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 assumptions on the data generating process to facilitate its identification from purely observational data. Continuing this line of research, we show how to discover the complete causal structure of continuous-valued data, under the assumptions that (a) the data generating process is linear, (b) there are no unobserved… CONTINUE READING
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