Estimation of causal orders in a linear non-Gaussian acyclic model: A method robust against latent confounders

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 7552 LNCS, Issue PART 1, 2012, Pages 491-498

  Tashiro, Tatsuya ^a   Shimizu, Shohei ^a   Hyvärinen, Aapo ^b   Washio, Takashi ^a  

^a OSAKA UNIVERSITY   (Japan)

^b UNIVERSITY OF HELSINKI   (Finland)

Author keywords

causal Bayesian networks; latent confounders; non Gaussianity

Indexed keywords

ARTIFICIAL DATA; CAUSAL BAYESIAN NETWORK; CAUSAL ORDER; CAUSAL ORDERING; ESTIMATION RESULTS; LATENT CONFOUNDERS; MODEL ASSUMPTIONS; NON-GAUSSIAN; NONGAUSSIANITY;

BAYESIAN NETWORKS; GAUSSIAN NOISE (ELECTRONIC); NEURAL NETWORKS;

ESTIMATION;

EID: 84867666606     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-33269-2_62     Document Type: Conference Paper

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