Perovskites are a class of materials with great potential as solar cells. UC Davis materials scientists have used machine learning to explore the wide variety of perovskite formulas to find those best ...

A global team of researchers has made strides in refining weather forecasting methods, with a specific focus on addressing the persistent issue of "quantile crossing." This phenomenon disrupts the ...

The search for next-generation electronic materials often starts with studying the Fermi surface, which serves as a map of a material's electronic structure. Its shape varies with crystal structure, ...

Researchers have determined how to build reliable machine learning models that can understand complex equations in real-world situations while using far less training data than is normally expected.

A new technical paper titled “Post-hoc Uncertainty Learning using a Dirichlet Meta-Model” was published (preprint) by researchers at MIT, University of Florida, and MIT-IBM Watson AI Lab (IBM Research ...

Microplastics – the tiny particles of plastic shed when litter breaks down – are everywhere, from the deep sea to Mount Everest, and many researchers worry that they could harm human health. I am a ...

The Stanford professor’s work gives autonomous systems new frameworks for tackling complex tasks. Robots and AI agents are still limited when it comes to learning new things. That’s exactly the ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...

Researchers at the University of California, Davis College of Engineering are using machine learning to identify new materials for high-efficiency solar cells. Using high-throughput experiments and ...

Hybrid perovskites are organic-inorganic molecules that have received a lot of attention over the past 10 years for their potential use in renewable energy. Some are comparable in efficiency to ...