The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...

Heart failure is a leading cause of hospitalization and long-term disability, with many individuals progressing from subclinical disease to overt symptoms ...

Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could dramatically slash the cost and energy required to develop new lithium-ion ...

High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, traditional methods like the R-ratio ...

Machine learning algorithms that output human-readable equations and design rules are transforming how electrocatalysts for ...

Machine learning can predict many things, but can it predict who will develop schizophrenia years before the average ...

Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...