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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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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-BB80-C Version Permalink: http://hdl.handle.net/21.11116/0000-0002-0AE9-D
Genre: Conference Paper

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 Creators:
Mooij, JM1, 2, Author              
Stegle, O1, 2, Author              
Janzing, D1, 2, Author              
Zhang, K1, 2, Author              
Schölkopf, B1, 2, Author              
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              

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 Abstract: 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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Language(s):
 Dates: 2011-06
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: BibTex Citekey: 6767
 Degree: -

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Title: Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010)
Place of Event: Vancouver, BC, Canada
Start-/End Date: 2010-12-06 - 2010-12-11

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Title: Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010
Source Genre: Journal
 Creator(s):
Lafferty, J, Editor
Williams, CKI, Editor
Shawe-Taylor, J, Editor
Zemel, RS, Editor
Culotta, A, Editor
Affiliations:
-
Publ. Info: Red Hook, NY, USA : Curran
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 1687 - 1695 Identifier: ISBN: 978-1-617-82380-0