American Institute of Physics

Predicting stroke recovery motor progress using EEG data

A machine learning model trained on EEG data from patients recovering from strokes helps predict how new patients will regain ...

Web-based tool visualizes catalyst 'gene' profiles to speed materials design

Modern industry relies heavily on catalysts, which are substances that speed up chemical reactions. They're vital in ...

Machine learning accelerates plasma mirror design for high-power lasers

Plasma mirrors capable of withstanding the intensity of powerful lasers are being designed through an emerging machine ...
InfoQ

Open Responses Specification Enables Unified Agentic LLM Workflows

OpenAI's Open Responses standardizes agentic AI workflows, tackling API fragmentation and enabling seamless transitions ...
IEEE

Metaheuristic-Based Hyperparameter Tuning for Pretrained Deep Learning Model: Application to the Skin Cancer Identification

Abstract: Computer-aided automated diagnosis is necessary due to the multifaceted nature of skin problems, the scarcity and uneven distribution of qualified dermatologists, and the requirements for ...
IEEE

Quantum Machine Learning: Recent Advances, Challenges, and Perspectives

Abstract: This study presents a comprehensive survey on Quantum Machine Learning (QML) along with its current status, challenges, and perspectives. QML combines quantum computing and machine learning ...