Abstract: Estimation of distribution algorithms (EDAs) face substantial difficulty in navigating complex landscapes efficiently due to predefined prior assumptions. Deep generative model-based EDAs ...
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 ...
This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...
Abstract: Large-scale industrial processes are characterized by complex reaction mechanisms and strong correlation among operational units, which makes it more difficult to extract the temporal ...