jiacheng-xu/vmf_vae_nlp
Code for EMNLP18 paper "Spherical Latent Spaces for Stable Variational Autoencoders"
This project offers an improved way to analyze and generate text using advanced probabilistic models. It takes large collections of text, like news articles or reviews, and processes them to identify underlying themes and relationships. The output is a more stable and accurate representation of text, which can be used by natural language processing researchers or data scientists working with text data.
171 stars. No commits in the last 6 months.
Use this if you are a researcher or practitioner in natural language processing looking for more robust variational autoencoder models for text analysis and generation.
Not ideal if you need a plug-and-play solution for general text classification or sentiment analysis without deep model customization.
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171
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17
Language
Python
License
MIT
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Last pushed
Dec 12, 2018
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