About the complexity of learning probabilistic graphical models

Question

I guess that one way of measuring the complexity of learning a joint probability distribution is as its "sample complexity" (which is also sometimes known as its "distributional learning complexity"?) I wanted to know if any computation of these measures are known for probabilistic graphical models.