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: In this paper, we introduce the `Reverse Variational Autoencoder" (Reverse-VAE) which is a generative network. On the one hand, visual attributes can be manipulated and combined while ...

Variational autoencoder architectures have the potential to develop reduced-order models for chaotic fluid flows. We propose a method for learning compact and near-orthogonal reduced-order models ...

Objective: Biomechanical Machine Learning (ML) models, particularly deep-learning models, demonstrate the best performance when trained using extensive datasets. However, biomechanical data are ...

In the past, linear dimensionality-reduction techniques, such as Principal Component Analysis, have been used to simplify the myoelectric control of high-dimensional prosthetic hands. Nonetheless, ...

1 Electrical and Computer Engineering, Lakehead University, Thunder Bay, Canada. 2 Automotive Engineering, Weifang College of Engineering, Qingzhou, China. 3 Mechanical Engineering, Lakehead ...