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About Deep Latent-Variable Models of Natural Language: Yoon Kim, Sam Wiseman, Alexander Rush
This document provides a tutorial on deep latent-variable models for natural language processing. It discusses how to reason about latent variables in NLP, challenges that arise from modeling text with latent variables, and techniques explored in recent papers. The tutorial covers deep latent-variable models, variational objectives, inference strategies, advanced techniques, example applications, and code samples. The goal is to explore these topics through the lens of variational inference.
Detailed Information
| Author: | ['rakesh'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 211 |
| Language: | English |
| Format: | |
| Price: | FREE |
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