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  Probabilistic latent variable models for distinguishing between cause and effect

Mooij, J., Stegle, O., Janzing, D., Zhang, K., & Schölkopf, B. (2011). Probabilistic latent variable models for distinguishing between cause and effect. Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010, 1687-1695.

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 Urheber:
Mooij, JM1, Autor           
Stegle, O2, Autor           
Janzing, D3, Autor           
Zhang, K1, Autor           
Schölkopf, B1, Autor           
Lafferty, Herausgeber
J., Herausgeber
Williams, C. K.I., Herausgeber
Shawe-Taylor, J., Herausgeber
Zemel, R. S., Herausgeber
Culotta, A., Herausgeber
Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795              

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 Zusammenfassung: We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y. The basic idea is to model the observed data using probabilistic latent variable models, which incorporate the effects of unobserved noise. To this end, we consider the hypothetical effect variable to be a function of the hypothetical cause variable and an independent noise term (not necessarily additive). An important novel aspect of our work is that we do not restrict the model class, but instead put general non-parametric priors on this function and on the distribution of the cause. The causal direction can then be inferred by using standard Bayesian model selection. We evaluate our approach on synthetic data and real-world data and report encouraging results.

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Sprache(n):
 Datum: 2011-06
 Publikationsstatus: Erschienen
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: ISBN: 978-1-617-82380-0
URI: http://nips.cc/Conferences/2010/
BibTex Citekey: 6767
 Art des Abschluß: -

Veranstaltung

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Titel: Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010)
Veranstaltungsort: Vancouver, BC, Canada
Start-/Enddatum: -

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Titel: Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010
Genre der Quelle: Zeitschrift
 Urheber:
Affiliations:
Ort, Verlag, Ausgabe: Red Hook, NY, USA : Curran
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 1687 - 1695 Identifikator: -