Topic models have been thoroughly investigated for multiple years due to their great potential in analyzing and understanding texts. Recently, researchers combine the study of topic with deep learning techniques, known as Neural Models (NTMs). However, existing NTMs are mainly tested based on general document modeling without considering different textual analysis scenarios. We assume that ther...

Topic models and all their variants analyse text by learning meaningful representations through word co-occurrences. As pointed out previous work, such implicitly assume that the probability of a topic to be active its proportion within each document are positively correlated. This correlation can strongly detrimental in case documents created over time, simply because recent likely better desc...