Accurately tracking atmospheric greenhouse gases requires not only fast predictions but also reliable estimates of uncertainty. Researchers have developed a lightweight machine learning framework that ...

By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.

Deep learning is increasingly used in financial modeling, but its lack of transparency raises risks. Using the well-known Heston option pricing model as a benchmark, researchers show that global ...

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.

In a new study published in Physical Review Letters, researchers used machine learning to discover multiple new classes of two-dimensional memories, systems that can reliably store information despite ...

As artificial intelligence explodes in popularity, two of its pioneers have nabbed the 2024 Nobel Prize in physics. The prize surprised many, as these developments are typically associated with ...

An artificial neural network, a type of artificial intelligence which can engage in machine learning, can be patented, the ...

Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas ...