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 ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of structured, siloed, and confidential data.

When designed well, agentic systems can reduce data silos. Static data, even when perfectly modeled, doesn’t move the needle for businesses on its own. Adaptive, autonomous intelligence makes ...

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 ...

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

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Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

Springer Nature is a signatory of the San Francisco Declaration on Research Assessment (DORA). Because small numbers of highly cited articles can have outsized influence on certain citation measures ...