From Autoencoders to Variational Autoencoders - Improving the Encoder

Explore the transformation of autoencoders into Variational Autoencoders (VAEs) in this informative video. Delve into the limitations of traditional autoencoders for generative tasks and discover how VAEs address these issues. Learn about multivariate normal distributions and their crucial role in encoding input data into a latent space for improved generative capabilities. Gain insights into the encoder mapping differences between autoencoders and VAEs, understand univariate and multivariate normal distributions, and explore how multivariate normal distributions solve discontinuities in VAEs. Perfect for those interested in deep learning and generative models in artificial intelligence and sound processing.

Intro
Issues with vanilla AEs
From AEs to VAEs
Encoder mapping: AEs vs VAEs
Univariate normal distribution
Multivariate normal distrivution
Usage of multivariate normal distribution in VAEs
How multivariate normal distribution solves discontinuities in VAEs