Abstract: This article proposes a new underwater thruster fault detection and identification method based on adversarial variational autoencoder (AdvVAE). Adversarial training and variational ...
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 focuses on learning useful representations from unlabelled data for downstream tasks, specifically categorizing images into one of N categories using Variational Autoencoders (VAE). The ...
This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...
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