To address these challenges, this study proposes a novel multi-rate dynamic variational autoencoder (MDVAE) model, specifically designed for dynamic industrial fault detection with incomplete dataset.

This repository contains a comprehensive implementation of Variational Autoencoders (VAEs) applied to two different image datasets: CIFAR-10 and Fashion-MNIST. The project demonstrates how dataset ...

autoencoder.py # Main VQ-VAE model implementation ... lpips.py # LPIPS perceptual loss implementation │ ├── unet.py # U-Net architecture for encoder/decoder │ └── utils/ │ └── utils.py # Utility ...

In this paper, we propose a novel recommendation framework named CVGAE (short for camouflaged variational graph autoencoder), which effectively models user behaviors and mitigates the risk of user ...

Now, researchers at MIT have developed an entirely new way of approaching these complex problems, using simple diagrams as a tool to reveal better approaches to software optimization in deep-learning ...

Wu et al. introduced an algorithm termed GAMCLDA, which is based on the principles of graph encoder matrix completion (Wu et al., 2020). This model effectively incorporates a wide range of biological ...