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 ...

This project will introduce the Variational Auto Encoder for processing images, using CelebA dataset in Python. The aim of this project is to introduce the Variational Auto Encoder, both theoretically ...

Abstract: This paper proposes a method to improve the performance of channel coding by using Auto Encoder. The channel coding technique used in this paper is the Golay code. The proposed method is to ...

Modern image and video generation methods rely heavily on tokenization to encode high-dimensional data into compact latent representations. While advancements in scaling generator models have been ...

Abstract: This paper presents a novel auto-encoder based end-to-end channel encoding and decoding. It integrates deep reinforcement learning (DRL) and graph neural networks (GNN) in code design by ...

Artificial neural networks (ANN) have gained significant attention in magnetotelluric (MT) inversions due to their ability to generate rapid inversion results compared to traditional methods. While a ...