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Review of variational autoencoders model
- 1 JILIN university, college of computer science, ChangChun, 334000, China
* Author to whom correspondence should be addressed.
Abstract
Variational autoencoder is one of the deep latent space generation models, which has become increasingly popular in image generation and anomaly detection in recent years. In this paper, we first review the development and research status of traditional variational autoencoders and their variants, and summarize and compare the performance of all variational autoencoders. then give a possible development direction of VAE.
Keywords
Variational Auto-Encoder, unsupervised learning, deep learning
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Cite this article
Liu,J. (2023). Review of variational autoencoders model. Applied and Computational Engineering,4,588-596.
Data availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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Volume title: Proceedings of the 3rd International Conference on Signal Processing and Machine Learning
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