Abstract: Variational autoencoder (VAE) is widely used as a data enhancement technique. However, it faces challenges with inaccurate potential spatial distribution and poor reconstruction quality when ...
Abstract: Accurate online detection or prediction of key quality variables provides critical reference information for optimizing and controlling operating variables in industrial processes. However, ...
This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...
This project implements a Variational Autoencoder (VAE) for generating face images from the CelebA dataset. The VAE learns a probabilistic latent representation of faces and can generate new faces by ...
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