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 ...

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 ...

This GitHub repository hosts implementations of Variational Autoencoder (VAE) and Denoising Convolutional VAE specifically designed for exploring protein-ligand interactions. - JMLab-tifrh ... strides ...

In this article, a conditional variational autoencoder based method is proposed for the probabilistic wind power curve modeling task. To advance the modeling performance, the latent random variable is ...

To summarize, the above results suggest that a variational autoencoder with 4 hidden layers in both of the encoder and decoder modules exhibited the best performance in terms of learning a meaningful ...