The latent dimension is the size of the vector that represents the compressed version of the input data in the VAE. The latent dimension affects how much information the VAE can encode and decode ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

Abstract: In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random ...

The project, titled "Variational Autoencoder for Fashion-MNIST Dataset," is a hands-on implementation of a VAE, a type of generative model that combines neural networks with Bayesian inference. VAEs ...