Examples include neural topic models which are typically built upon variational autoencoder (VAE) with an objective of minimising the error of reconstructing original documents based on the learned latent topic vectors.
we evaluate our model on the 20 Newsgroups † consisting of 18K documents, and NIPS (Tan  et al., 2017) consisting of 6.6k documents.