Graph out-of-distribution (OOD) generalization remains a major challenge in graph neural networks (GNNs). Invariant learning, aiming to extract invariant features across varied distributions, has ...

Like many of us, [Tim]’s seen online videos of circuit sculptures containing illuminated LED filaments. Unlike most of us, however, he went a step further by using graph theory to design glowing ...

To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated.

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 an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

Text mining and knowledge graphs connect cell-culture parameters to glycosylation for faster bioprocess optimization.

There is a developed method to rank the severity of our winter. Let’s look to see if this winter has really been as harsh as ...

These are two examples of how climate scientists manipulate data to generate scary-looking charts. Global warming is real, ...

Eucalyptus trees, laden with flammable oils, could spread into Portugal's south-central region by 2060 if changing climate ...

A just-released study reexamines whether the body compensates for exercise by conserving energy elsewhere—and why diet may ...

Astronomers have announced the discovery of what appears to be an "ice cold Earth," a chilly but potentially habitable rocky ...