Deep-learning (DL)-based channel state information (CSI) feedback has attracted a great deal of attention due to its effectiveness in compressing CSI in massive multiple-input multiple-output systems.

VAE on Simple Autoencoder This repository contains the implementation of Variational Autoencoders (VAEs) using simple autoencoder architectures on various datasets. VAEs are a type of neural network ...

A variational autoencoder (VAE) is a deep neural system that can be used to generate synthetic data. VAEs share some architectural similarities with regular neural autoencoders (AEs) but an AE is not ...

ITF-VAE: Variational Auto-Encoder using interpretable continuous time series features ... Therefore, we present a novel variational autoencoder approach to generate time series data on a probabilistic ...

This project implements a Variational Autoencoder (VAE) to reconstruct and generate handwritten digits from the MNIST dataset. The VAE is a probabilistic generative model designed to learn a latent ...