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Inferring deterministic causal relations

2010

Conference Paper

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We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.

Author(s): Daniusis, P. and Janzing, D. and Mooij, J. and Zscheischler, J. and Steudel, B. and Zhang, K. and Schölkopf, B.
Book Title: Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence
Journal: Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Sixth Conference (UAI 2010)
Pages: 143-150
Year: 2010
Month: July
Day: 0
Editors: P Gr{\"u}nwald and P Spirtes
Publisher: AUAI Press

Department(s): Empirical Inference
Research Project(s): Causality (Causal Inference)
Bibtex Type: Conference Paper (inproceedings)

Event Name: UAI 2010
Event Place: Catalina Island, CA, USA

Address: Corvallis, OR, USA
Digital: 0
ISBN: 978-0-9749039-6-5
Language: en
Organization: Max-Planck-Gesellschaft
School: Biologische Kybernetik

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BibTex

@inproceedings{6620,
  title = {Inferring deterministic causal relations},
  author = {Daniusis, P. and Janzing, D. and Mooij, J. and Zscheischler, J. and Steudel, B. and Zhang, K. and Sch{\"o}lkopf, B.},
  journal = {Uncertainty in Artificial Intelligence: Proceedings of the Twenty-Sixth Conference (UAI 2010)},
  booktitle = {Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence},
  pages = {143-150},
  editors = {P Gr{\"u}nwald and P Spirtes},
  publisher = {AUAI Press},
  organization = {Max-Planck-Gesellschaft},
  school = {Biologische Kybernetik},
  address = {Corvallis, OR, USA},
  month = jul,
  year = {2010},
  month_numeric = {7}
}