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Information Flows in Causal Networks
Nihat Ay and Daniel Polani
We introduce a notion of causal independence based on virtual intervention, which is a fundamental concept of the theory of causal networks. Causal independence allows for defining a measure for the strength of a causal effect. We call this information flow and compare it with known information flow measures such as the transfer entropy.