SMMSN can not only fuse multi-level data representations of single omics data by Graph Convolutional Network (GCN) and Stacked Autoencoder Network (SAE ... they were implemented by MATLAB 2022a ...

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 ...

In this paper, we propose the adversarial attention variational graph autoencoder (AAVGA), which is a novel framework that incorporates attention networks into the encoder part and uses an adversarial ...

The team proposes an explicit and interpretable discrete variational auto-encoder model for generating efficiency-improving code transformations. They demonstrate that this model can be trained from a ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...