Before revision:  However, modelers often use sampling methods to estimate intractable expectations such as in Reinforcement Learning and Variational Inference.
After revision:  Stochastic AD extends AD to stochastic computation graphs with sampling steps, which arise when modelers handle the intractable expectations common in Reinforcement Learning and Variational Inference.