Nature

Antenna optimization using machine learning with reduced-dimensionality surrogates

In modern times, antenna design has become more demanding than ever. The escalating requirements for performance and functionality drive the development of intricately structured antennas, where ...
Nature

Cost-efficient variable-fidelity machine learning for globalized optimization of microwave structures

This paper proposes a novel methodology for cost-efficient optimization of microwave circuits. The design task at hand is the identification of the solution that minimizes the assumed scalar cost ...
Visual Studio Magazine

Data Dimensionality Reduction Using a Neural Autoencoder with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on creating an approximation of a dataset that has fewer columns. Imagine that you have a dataset that has many ...
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 ...