Nature

Hybrid machine learning and Gaussian process for antenna parameter estimation

This paper presents a hybrid method of combining the Random Forest (RF) algorithm in machine learning (ML) and the Gaussian process (GP) to design microstrip patch antennas at any frequency from 0.6 ...
Nature

Developing a hybrid machine learning model to predict treatment time duration as a workflow regulation tool in public and private dental clinics

This study aimed to design a desktop application that implements machine learning algorithms to predict dental treatment time durations, assess the accuracy of the model, and assess its clinical ...
Forbes

Hybrid Quantum: Classical Architectures For Machine Learning

Integrating quantum computing into AI doesn’t require rebuilding neural networks from scratch. Instead, I’ve found the most effective approach is to introduce a small quantum block—essentially a ...
AZoNano

Machine Learning Reveals Hidden Nanophotonic Resonances In Silicon-Gold Nanopillars

Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...