Variational Autoencoder | Introduction and Workshop

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 https://towardsdatascience.com/unders... https://www.tensorflow.org/tutorials/... https://keras.io/examples/generative/... Slides https://docs.google.com/presentation/... Script https://github.com/brandonyph/LiquidB... Email: liquidbrain.r@gmail.com Website: https://www.liquidbrain.org/videos Patreon:   / liquidbrain