When you listen to quantum enthusiasts, you may feel tempted to treat QML as an emerging silver bullet, which it isn’t.

Advances in machine learning for materials science, data-driven materials prediction, autonomous synthesis and characterization, and data-guided high-throughput exploration, can now significantly ...

Two new studies from the Department of Computational Biomedicine at Cedars-Sinai are advancing what we know about using ...

If you rotate an image of a molecular structure, a human can tell the rotated image is still the same molecule, but a machine ...

Upon completion of this course, participants should be able to: ¿ Understand how big data and machine learning can complement traditional data and analytical techniques in macroeconomic analysis and ...

In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization and applications of optimization in machine learning. About the Purdue ...

EMBL-EBI scientists and collaborators at Heidelberg University have developed CORNETO, a new computational tool that uses ...