PB VCR to provide a personalized video representation of each consumer’s credit report • Actionable insights along ...

ABSTRACT: Predicting molecular properties is essential for advancing for advancing drug discovery and design. Recently, Graph Neural Networks (GNNs) have gained prominence due to their ability to ...

Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...

This GitHub repository contains two directories : (1) variational autoencoder (VAE) and (2) denoising convolutional VAE (DCVAE). This contains programs for VAE and DCVAE models used in our work. For ...

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 ...

Abstract: 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 ...

The dimension of the latent space is set to 2. The variational autoencoder with 4 hidden layers performed the best with high Spearman and Pearson coefficients and low RMSD. To further evaluate the ...