Different from existing work, our model combines a sequence modeling component and a topic modeling component so that the final latent code of our model contains both topic semantics and sequential structure of texts.
our model can learn these two features simultaneously, since AutoEncoding Variation Bayes (AEVB) are employed to train these two components.