Variational Autoencoder (VAE) for MNIST This repository contains a Variational Autoencoder (VAE) implementation using PyTorch. The VAE learns to encode MNIST handwritten digits into a latent space and ...

This project demonstrates the use of a Variational AutoEncoder (VAE) to learn a latent space representation of simple synthetic data: black-and-white images of circles with varying radius, x, and y ...

2.3 Multi-Domain Variational Autoencoder. In order to capture the combined anatomy and ECG data obtained from the preprocessing steps, we propose a multi-domain β-VAE (Higgins et al., 2017) ...

The latent variable prior of the variational autoencoder (VAE) often utilizes a standard Gaussian distribution because of the convenience in calculation, but has an underfitting problem. This paper ...

The latent variable prior of the variational autoencoder (VAE) often utilizes a standard Gaussian distribution because of the convenience in calculation, but has an underfitting problem. This paper ...