Title
Consistency of Causal Inference under the Additive Noise Model.
Abstract
We analyze a family of methods for statistical causal inference from sample under the so-called Additive Noise Model. While most work on the subject has concentrated on establishing the soundness of the Additive Noise Model, the statistical consistency of the resulting inference methods has received little attention. We derive general conditions under which the given family of inference methods consistently infers the causal direction in a nonparametric setting.
Year
Venue
DocType
2013
ICML
Journal
Volume
Citations 
PageRank 
abs/1312.5770
3
0.41
References 
Authors
8
4
Name
Order
Citations
PageRank
Samory Kpotufe19211.56
Eleni Sgouritsa2564.57
Dominik Janzing372365.30
Bernhard Schölkopf4231203091.82