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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 ...
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