2015
BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions
NeurIPS 2015poster
We propose a simple method to learn linear causal cyclic models in the presence of latent variables. The method relies on equilibrium data of the model recorded under a specific kind of interventions (``shift interventions''). The location and strength of these interventions do not have to be known…