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Found 3 papers, 2 papers with code
Tree-Structured Topic Modeling with Nonparametric Neural Variational Inference
Topic modeling has been widely used for discovering the latent semantic structure of documents, but most existing methods learn topics with a flat structure.
Context Reinforced Neural Topic Modeling over Short Texts
As one of the prevalent topic mining tools, neural topic modeling has attracted a lot of interests for the advantages of high efficiency in training and strong generalisation abilities.
Neural Mixed Counting Models for Dispersed Topic Discovery
Mixed counting models that use the negative binomial distribution as the prior can well model over-dispersed and hierarchically dependent random variables; thus they have attracted much attention in mining dispersed document topics.
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