Abstract
Variational autoencoders provide a principled framework for learning deep\nlatent-variable models and corresponding inference models. In this work, we\nprovide an introduction to variational autoencoders and some important\nextensions.\n
Keywords
Latent variableInferenceArtificial intelligenceComputer scienceMachine learningDeep learningAutoencoderVariable (mathematics)Mathematics
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Publication Info
- Year
- 2019
- Type
- article
- Volume
- 12
- Issue
- 4
- Pages
- 307-392
- Citations
- 2194
- Access
- Closed
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Cite This
Diederik P. Kingma,
Max Welling
(2019).
An Introduction to Variational Autoencoders.
Foundations and Trends® in Machine Learning
, 12
(4)
, 307-392.
https://doi.org/10.1561/2200000056
Identifiers
- DOI
- 10.1561/2200000056
- arXiv
- 1906.02691