# Distinguishing Cause and Effect via Second Order Exponential Models

@article{Janzing2009DistinguishingCA, title={Distinguishing Cause and Effect via Second Order Exponential Models}, author={D. Janzing and Xiaohai Sun and B. Schoelkopf}, journal={arXiv: Machine Learning}, year={2009} }

We propose a method to infer causal structures containing both discrete and continuous variables. The idea is to select causal hypotheses for which the conditional density of every variable, given its causes, becomes smooth. We define a family of smooth densities and conditional densities by second order exponential models, i.e., by maximizing conditional entropy subject to first and second statistical moments. If some of the variables take only values in proper subsets of R^n, these… Expand

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