This repository contains a comprehensive implementation of Variational Autoencoders (VAEs ... The implementation achieves successful image generation and reconstruction on both datasets, with better ...

This repository contains a Jupyter notebook implementing a Vanilla Variational Autoencoder (VAE) for image generation. The VAE is a powerful generative model that learns to encode images into a latent ...

Abstract: The Vector Quantized Variational AutoEncoder (VQ-VAE) has shown great potential in image generation, especially the methods with hierarchical features. However, the lack of decoupling of ...

Each image is 8 by 8 pixel values between 0 and 16 ... The design pattern presented here will work for most variational autoencoder data generation scenarios. If your raw data contains a categorical ...

In this paper a novel Variational Autoencoder (VAE) architecture is proposed for WCE image synthesis, namely ‘This Intestine ... Its advantage is that it enables the generation of high-quality and ...

A variational autoencoder produces a probability distribution for ... data denoising, feature extraction, image generation, sequence to sequence prediction, and recommendation systems. Data denoising ...