In this paper, we propose a novel, model-free robust state estimator based on the conditional variational autoencoder (CVAE). Unlike traditional model-based methods such as weighted least squares, our ...

Toy example for a Conditional Variational Autoencoder in Keras. Regresses features from automatically generated images. Useful for learning about the concept. python machine-learning ...

A Conditional Variational Autoencoder (CVAE) extends the concept of a Variational Autoencoder (VAE) by incorporating a conditional variable into both its encoder and decoder components.

In this article, we present AEGANAuth, a lightweight and effective autoencoder GAN (AEGAN)-based continuous Authentication system for mobile devices using conditional variational autoencoder ...

A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data ...

Conditional Variational Autoencoder (CVAE) on MNIST. This project implements a Conditional VAE trained on MNIST to generate digits conditioned on labels. 🧠 Features. Conditional image generation ...

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.