Information-geometric approach to inferring causal directions

Artificial Intelligence

Volumn 182-183, Issue , 2012, Pages 1-31

  Janzing, Dominik ^a   Mooij, Joris ^b   Zhang, Kun ^a   Lemeire, Jan ^c,d   Zscheischler, Jakob ^a   Daniušis, Povilas ^e   Steudel, Bastian ^f   Schölkopf, Bernhard ^a  

^a MAX PLANCK INSTITUTE FOR INTELLIGENT SYSTEMS   (Germany)

^b RADBOUD UNIVERSITY NIJMEGEN   (Netherlands)

^c VRIJE UNIVERSITEIT BRUSSEL   (Belgium)

^d Interdisciplinary Institute for Broadband Technology   (Belgium)

^e VILNIUS UNIVERSITY   (Lithuania)

^f MAX PLANCK INSTITUTE FOR MATHEMATICS IN THE SCIENCES   (Germany)

Author keywords

Cause effect pairs; Deterministic causal relations; Pythagorean triple

Indexed keywords

CAUSAL RELATIONS; CAUSE-EFFECT; CONDITIONAL DISTRIBUTION; CONVENTIONAL APPROACH; INFERENCE METHODS; INFORMATION SPACES; JOINT DISTRIBUTIONS; KOLMOGOROV COMPLEXITY; MARGINAL DISTRIBUTION; ORTHOGONALITY; PRACTICAL IMPLEMENTATION; PYTHAGOREAN TRIPLE; THEORETICAL RESULT;

ARTIFICIAL INTELLIGENCE;

EID: 84857129458     PISSN: 00043702     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.artint.2012.01.002     Document Type: Article

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