This project demonstrates the use of a Variational AutoEncoder (VAE) to learn a latent space representation of simple synthetic data: black-and-white images of circles with varying radius, x, and y ...

The latent variable prior of the variational autoencoder (VAE) often utilizes a standard Gaussian distribution because of the convenience in calculation, but has an underfitting problem. This paper ...

A Conditional Variational Autoencoder (CVAE) is a specialized type of Variational Autoencoder (VAE) that integrates a conditional variable into both the encoder and decoder.

2.2. Variational Autoencoder (VAE) The VAE is a generative model that learns a probabilistic representation of the input data. It consists of an encoder where q 0 (z | x) and the decoder p 0 (z | x), ...

This project demonstrates the use of a Variational AutoEncoder (VAE) to learn a latent space representation of simple synthetic data: black-and-white images of circles with varying radius, x, and y ...

The latent variable prior of the variational autoencoder (VAE) often utilizes a standard Gaussian distribution because of the convenience in calculation, but has an underfitting problem. This paper ...

Aprenda a implementar un VAE condicional, un modelo generativo que puede producir datos basados en condiciones. Descubra los beneficios de agregar etiquetas a la entrada y salida.