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  Distinguishing cause from effect using observational data: methods and benchmarks

Mooij, J., Peters, J., Janzing, D., Zscheischler, J., & Schölkopf, B. (2016). Distinguishing cause from effect using observational data: methods and benchmarks. The Journal of Machine Learning Research, 17(1), 1103-1204. Retrieved from http://dl.acm.org/citation.cfm?id=2946645.2946677.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-002D-1980-D Version Permalink: https://hdl.handle.net/21.11116/0000-0004-74F8-2
Genre: Journal Article

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 Creators:
Mooij, J.M.1, Author
Peters, J.2, Author           
Janzing, D.2, Author           
Zscheischler, J.1, Author
Schölkopf, B2, Author           
Affiliations:
1External Organizations, ou_persistent22              
2Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497647              

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Free keywords: Abt. Schölkopf
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Language(s): eng - English
 Dates: 2016-01
 Publication Status: Issued
 Pages: -
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 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: Mooijetal16
URI: http://dl.acm.org/citation.cfm?id=2946645.2946677
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Title: The Journal of Machine Learning Research
Source Genre: Journal
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Publ. Info: Cambridge, MA : MIT Press
Pages: - Volume / Issue: 17 (1) Sequence Number: - Start / End Page: 1103 - 1204 Identifier: ISSN: 1532-4435
CoNE: https://pure.mpg.de/cone/journals/resource/111002212682020_1