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 ...
Semiconductor Engineering

AI Models Transform Defect Inspection And Review, But Can Fail To Scale

AI plays a role in improving defect capture rate and distinguishing between yield-killing and nuisance defects. New developments in wafer edge inspection are proving essential to bonded wafer yields.
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...