Keeping long-term climate simulations stable and accurate with a new AI approach

Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving ...
IEEE

A Wasserstein Distributionally Robust Multiclass Support Vector Machine for Industrial Fault Diagnosis

Abstract: Modern fault diagnosis models that rely on machine learning and AI tools have been beset by three key challenges: first, highly uncertain training data due to sensor noise and potentially ...
The Conversation

Machines whisper before they scream: we built an AI model that predicts expensive problems

Edward Khomotso Nkadimeng receives funding from the National Research Foundation. In most industries, maintenance is a waiting game. Things are fixed when they break. But in the 21st century, an age ...
InfoWorld

How to deploy machine learning models with AWS Lambda

AWS Lambda provides a simple, scalable, and cost-effective solution for deploying AI models that eliminates the need for expensive licensing and tools. In the rapidly evolving landscape of artificial ...
C&EN

Machine learning helps density functional theory model molecules accurately

A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
IEEE

Quantum Machine Learning for Image Classification: A Hybrid Model of Residual Network with Quantum Support Vector Machine

Abstract: Recently, there has been growing attention on combining quantum machine learning (QML) with classical deep learning approaches as computational techniques are key to improving the ...
Frontiers

Support vector machine-based classification of bulimia nervosa using diffusion tensor imaging

Background: Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging ...
Frontiers

Assessing the learning potential of freshmen in labor education courses using ordinal features and support vector machine

Introduction: Artificial intelligence (AI) marks a new wave of the information technology revolution and permeates various sectors as an indispensable tool. Despite its widespread adoption, its ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...