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, NIPS 2010

Volumn , Issue , 2010, Pages

  Mooij, Joris M ^a   Stegle, Oliver ^a   Janzing, Dominik ^a   Zhang, Kun ^a   Schölkopf, Bernhard ^a  

^a MAX PLANCK INSTITUTE FOR BIOLOGICAL CYBERNETICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EQUIVALENCE CLASSES;

BAYESIAN MODEL SELECTION; CAUSE AND EFFECTS; INDEPENDENT NOISE; LATENT VARIABLE MODELING; NOISE TERMS; NONPARAMETRICS; NOVEL METHODS; OBSERVED DATA; PROBABILISTICS; SYNTHETIC DATA;

BAYESIAN NETWORKS;

EID: 85162054206     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

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