An autoencoder is a type of unsupervised neural network that learns to represent input data in a compressed latent space. This compressed representation captures the essential features of the data ...

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. Usage The script first loads the MNIST dataset and normalizes the ...

Abstract: Autoencoders have proven successful across diverse applications such as data reconstruction, anomaly detection, and feature extraction, however, these advancements remain largely dispersed ...