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 ...

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.

The massive datasets that power machine learning algorithms and systems are complex, noisy, and vulnerable to various kinds of errors, contamination, and adversarial corruptions. As data science and ...

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 ...

Digital twins and prognostic models deliver detailed insights into a battery’s behaviour and lifespan, and machine learning..

Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...

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 ...

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 ...