Variational Autoencoder is a more advance version of autoencoder. Instead of storing the latent vector directly in the neural network, it added another layer of gaussian function to allow for a more general representation of those latent vector. Typically, it allows for a better generation of data than GAN in certain situation. In this video I tried to walkthrough some basic introduction of VAE, how to make them in R, and how they were used in research.

References
[ Ссылка ]
[ Ссылка ]
[ Ссылка ]

Slides
[ Ссылка ]

Script
[ Ссылка ]

Email: liquidbrain.r@gmail.com
Website: [ Ссылка ]
Patreon: [ Ссылка ]

свернуть