Natural Language Generation (NLG) has made great progress in recent years due to the
development of deep learning techniques such as pre-trained language models. This …

We address a new numerical method based on a class of machine learning methods, the so-
called Extreme Learning Machines (ELM) with both sigmoidal and radial-basis functions, for …

The task of recognizing human facial expressions plays a vital role in various human-related
systems, including health care and medical fields. With the recent success of deep learning …

There has been a massive increase in research interest towards applying data driven
methods to problems in mechanics, with a particular emphasis on using data driven …

Commonsense question answering requires reasoning about everyday situations and
causes and effects implicit in context. Typically, existing approaches first retrieve external …

Image-to-Image translation in Generative Artificial Intelligence (Generative AI) has been a
central focus of research, with applications spanning healthcare, remote sensing, physics …

Continual Learning (CL) is a process in which there is still huge gap between human and
deep learning model efficiency. Recently, many CL algorithms were designed. Most of them …

Artificial neural network (ANN) has been widely used in automation. However, the
vulnerability of ANN under certain attacks poses a security threat to critical automation …

In this paper, we present an efficient energy stable finite element method for the two phase
incompressible Magnetohydrodynamic (MHD) flow which is governed by the incompressible …

In this study we present AI Prediction of Equatorial Plasma Bubbles (APE), a machine
learning model that can accurately predict the Ionospheric Bubble Index (IBI) on the Swarm …