Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

An artificial-intelligence algorithm that discovers its own way to learn achieves state-of-the-art performance, including on some tasks it had never encountered before. Joel Lehman is at Lila Sciences ...

ABSTRACT: Egg loss is one of the major problems in the egg hatching industry. This study aims to support farmers in optimizing their egg hatch through the development of a prediction model. This is to ...

Abstract: This paper presents a deep learning (DL) based method for 3D rotation prediction on point cloud data. The proposed approach utilizes a single graph convolutional layer to capture meaningful ...

This repository contains my implementation of the Hybrid Input-Output (HIO) algorithm for phase retrieval — recovering phase information from Fourier magnitude data, a key problem in computational ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most difficult tasks in numerical ...

Abstract: Placement algorithms for analog circuits explore numerous layout configurations in their iterative search. To steer these engines towards layouts that meet the electrical constraints on the ...

For the past two decades, researchers have attempted to create a Quantum Neural Network (QNN) by combining the merits of quantum computing and neural computing. In order to exploit the advantages of ...