An Introduction to Variational Autoencoders
arXiv:1906.02691v33041 citations
AI Analysis
It serves as an introductory resource for researchers and practitioners in machine learning, presenting established methods without new contributions.
The paper introduces variational autoencoders as a framework for learning deep latent-variable models and inference models, covering basic concepts and key extensions.
Variational autoencoders provide a principled framework for learning deep latent-variable models and corresponding inference models. In this work, we provide an introduction to variational autoencoders and some important extensions.