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

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 ...

(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 ...

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 ...

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 ...