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» Nonlinear causal discovery with additive noise models
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NIPS
2008
12 years 3 months ago
Nonlinear causal discovery with additive noise models
The discovery of causal relationships between a set of observed variables is a fundamental problem in science. For continuous-valued data linear acyclic causal models with additiv...
Patrik O. Hoyer, Dominik Janzing, Joris M. Mooij, ...
PKDD
2009
Springer
196views Data Mining» more  PKDD 2009»
12 years 8 months ago
Causality Discovery with Additive Disturbances: An Information-Theoretical Perspective
We consider causally sufficient acyclic causal models in which the relationship among the variables is nonlinear while disturbances have linear effects, and show that three princi...
Kun Zhang, Aapo Hyvärinen
JMLR
2008
144views more  JMLR 2008»
12 years 1 months ago
Search for Additive Nonlinear Time Series Causal Models
Pointwise consistent, feasible procedures for estimating contemporaneous linear causal structure from time series data have been developed using multiple conditional independence ...
Tianjiao Chu, Clark Glymour
KDD
2009
ACM
230views Data Mining» more  KDD 2009»
12 years 6 months ago
Grouped graphical Granger modeling methods for temporal causal modeling
We develop and evaluate an approach to causal modeling based on time series data, collectively referred to as“grouped graphical Granger modeling methods.” Graphical Granger mo...
Aurelie C. Lozano, Naoki Abe, Yan Liu, Saharon Ros...
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