EEG Data Augmentation using Variational Autoencoder This repository contains the implementation of a variational autoencoder (VAE) for generating synthetic EEG signals, and investigating how the ...

We propose QuakeVAE, a variational autoencoder as a dataset augmentation technique for frequency-domain lunar seismic data. We also propose QuakeCNN , a convolutional neural network, to classify over ...

Variational Autoencoder as a Data Augmentation tool for Confocal Microscopy Images Abstract: Retinoblastoma is an ocular tumor characterized by malignant cells in the retina of the eye. For its ...

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 ...