TopicRNN is a generative model for documents that: 1. Draws a topic vector from a standard normal distribution and uses it to generate words in a document. 2. Computes a lower bound on the log marginal likelihood of words and stop word indicators. 3. Approximates the expected values in the lower bound using samples from an inference network that models the approximate posterior distribution over topics.