Deep generative models such as the generative adversarial network (GAN) and the variational autoencoder (VAE) have obtained increasing attention in a wide variety of applications. Nevertheless, the ...

Variational Autoencoder (VAE): A VAE compresses data into a compact form and then reconstructs it, enhancing data generation and modification.

Variational Autoencoders (VAE) simplify this process. VAEs are a type of autoencoder that compress input data into a latent space while adding a probabilistic twist.

In this paper, we present AEGANAuth, a lightweight and effective AutoEncoder GAN-based continuous Authentication system for mobile devices using conditional variational AutoEncoder Generative ...

In this article, we propose a self-augmentation strategy for improving ML-based device modeling using variational autoencoder (VAE)-based techniques. These techniques require a small number of ...

Category: Vision Language Vector Quantised-Variational AutoEncoder (VQ-VAE) is a generative model that aims to learn useful representations without supervision. It differs from traditional Variational ...

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 ...