











• 
It
is easy to generate an



unbiased
example at the leaf



nodes.



• 
It is
typically hard to compute



the
posterior distribution over



all
possible configurations of



hidden
causes. It is also hard



to
compute the probability of



an
observed vector.



• 
Given
samples from the



posterior,
it is easy to learn the


conditional
probabilities that



define
the model.

