A team of researchers at Queen's University has developed a powerful new kind of computing machine that uses light to take on ...

Using advanced computer simulations, researchers from the University of Rhode Island's Graduate School of Oceanography (GSO) ...

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 ...

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

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

At CES, what stood out to me was just how much Nvidia and AMD focused on a systems approach, which may be the most ...

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

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

Prism aims to move ChatGPT into scientific writing as OpenAI signals plans to share in future profits. Some are warning ...

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 ...

The Kennedy College of Science, Richard A. Miner School of Computer & Information Sciences, invites you to attend a doctoral dissertation proposal defense by Nidhi Vakil, titled: "Foundations for ...

For half a century, computing advanced in a reassuring, predictable way. Transistors—devices used to switch electrical ...