In the pursuit of magnesium (Mg) alloys with targeted mechanical properties, a multi-objective Bayesian optimisation workflow is presented to enable optimal Mg-alloy design. A probabilistic Gaussian ...

Hyperparameter optimization lies at the core of developing robust and reliable machine learning models. Unlike parameters learned during training, hyperparameters are set prior to the learning process ...

(Nanowerk News) Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon ...

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

Researchers at the University of Toronto's Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the ...

Add Yahoo as a preferred source to see more of our stories on Google. Researchers have developed high-performance nano-architected materials that have the strength of carbon steel but the lightness of ...

Researchers at the University of Toronto’s Faculty of Applied Science & Engineering have used machine learning to design nano-architected materials that have the strength of carbon steel but the ...