1 min readfrom Towards Data Science

Variational Autoencoders (VAEs) Explained: From Theory to ELBO and the Reparameterization Trick

Variational Autoencoders (VAEs) Explained: From Theory to ELBO and the Reparameterization Trick

A clear, math-first walkthrough of how VAEs learn to generate new data

The post Variational Autoencoders (VAEs) Explained: From Theory to ELBO and the Reparameterization Trick appeared first on Towards Data Science.

Want to read more?

Check out the full article on the original site

View original article

Tagged with

#Variational Autoencoders
#VAEs
#Generative Models
#Data Generation
#ELBO
#Evidence Lower Bound
#Reparameterization Trick
#Machine Learning
#Deep Learning
#Neural Networks
#Autoencoders
#Variational Inference
#Probability Distributions
#Latent Space
#Mathematical Theory
#Optimization
#Towards Data Science
#Data Science
#Algorithms
#Modeling