  Causal models with unobserved variables impose nontrivial constraints on the
distributions over the observed variables. When a common cause of two variables
is unobserved, it is impossible to uncover the causal relation between them
without making additional assumptions about the model. In this work, we
consider causal models with a promise that unobserved variables have known
cardinalities. We derive inequality constraints implied by d-separation in such
models. Moreover, we explore the possibility of leveraging this result to study
causal influence in models that involve quantum systems.
