This repository contains a complete implementation of a Vanilla Autoencoder, covering its architecture, theory, and real-world applications. Learn how to compress and reconstruct data using deep ...

To test this, we developed a compositional autoencoder (CAE) that decomposes high-dimensional data into distinct genotype-specific and environment-specific latent features. Our CAE framework employed ...

This repository contains a Jupyter notebook implementing a Vanilla Variational Autoencoder (VAE) for image generation. The VAE is a powerful generative model that learns to encode images into a latent ...

A Winner- Take-All convolutional autoencoder is applied to improve the performance on the half space radar high resolution range profile (HRRP) target recognitio ...

This study explores the feasibility of deploying an autoencoder-based IDS [2] for CAN BUS networks in resourceconstrained automotive environments. Unlike conventional deep learning approaches that ...