Nature

Training all-mechanical neural networks for task learning through in situ backpropagation

Recent advances unveiled physical neural networks as promising machine learning platforms, offering faster and more energy-efficient information processing. Compared with extensively-studied optical ...
Phys.org

Using machine learning to infer rules for designing complex mechanical metamaterials

Mechanical metamaterials are sophisticated artificial structures with mechanical properties that are driven by their structure, rather than their composition. While these structures have proved to be ...
ACHR News

Machine Learning for Making Machines: Applying Visual Search to Mechanical Parts

Computer vision researchers use machine learning to train computers in visually recognizing objects but very few apply machine learning to mechanical parts, such as gearboxes, bearings, brakes, ...
Nature

Data-driven prediction on critical mechanical properties of engineered cementitious composites based on machine learning

The present study introduces a novel approach utilizing machine learning techniques to predict the crucial mechanical properties of engineered cementitious composites (ECCs), spanning from typical to ...