  A causal model is an abstract representation of a physical system as a
directed acyclic graph (DAG), where the statistical dependencies are encoded
using a graphical criterion called `d-separation'. Recent work by Wood &
Spekkens shows that causal models cannot, in general, provide a faithful
representation of quantum systems. Since d-separation encodes a form of
Reichenbach's Common Cause Principle (RCCP), whose validity is questionable in
quantum mechanics, we propose a generalised graph separation rule that does not
assume the RCCP. We prove that the new rule faithfully captures the statistical
dependencies between observables in a quantum network, encoded as a DAG, and is
consistent with d-separation in a classical limit. We note that the resulting
model is still unable to give a faithful representation of correlations
stronger than quantum mechanics, such as the Popescu-Rorlich box.
