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 ...

This project presents a comprehensive implementation of a Variational Autoencoder system designed for unsupervised anomaly detection in high-dimensional datasets. The implementation emphasizes ...

Abstract: This study introduces a novel approach that combines a variational autoencoder and Bayesian optimization to accelerate the simultaneous parameter and topology optimization of interior ...

画像生成AIにおける「VAE（変分オートエンコーダ）」について、深く掘り下げていきます。VAEは、AIが新しい画像を生成する際に非常に重要な役割を果たす技術です。本記事では、初心者でも理解しやすいようにVAEを解説し、画像生成のプロセスをわかり ...

Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...

Abstract: In this paper, we address passive intermodulation (PIM) interference in heterogeneous fifth-generation ($\mathbf{5 G}$) networks, compounded by limited datasets and non-independent, ...