This repository contains the implementation, benchmarks, and supporting tools for my MSc dissertation project: Self-learning Variational Autoencoder for EEG Artifact Removal (Key code only). Benchmark ...

Abstract: Variational Autoencoder(VAE) combines the ideas of autoencoders and variational inference, introducing the concept of latent space and variational inference to endow autoencoders to generate ...

Matthew is a journalist in the news department at GameRant. He holds a Bachelor's degree in journalism from Kent State University and has been an avid gamer since 1985. Matthew formerly served as a ...

This repository contains the code and models used in the paper "Understanding European Heatwaves with Variational Autoencoders" submitted to Earth System Dynamics ...

Constantine Quantum Technologies, Frères Mentouri University Constantine 1, Ain El Bey Road, Constantine 25017, Algeria Laboratoire de Physique Mathématique et Subatomique, Frères Mentouri University ...

Introduction: Biomechanical changes due to aging increase the oxygen consumption of walking by over 30%. When this is coupled with reduced oxygen uptake capacity, the ability to sustain walking ...

Neural networks are designed to learn compressed representations of high-dimensional data, and autoencoders (AEs) are a widely-used example of such models. These systems employ an encoder-decoder ...

Recent advances in feature selection methods for breast cancer recurrence prediction: A systematic review. This is an ASCO Meeting Abstract from the 2025 ASCO Annual Meeting I. This abstract does not ...