Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...

Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025 ...

The 2024 Nobel Prize in Chemistry was recently granted to David Baker, Demis Hassabis and John M. Jumper, renowned for their pioneering works in protein design. In addition, Nature has recently ...

In an increasingly interconnected world, understanding the behavior and structure of complex networks has become essential across disciplines. These ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

David Beer’s book The Tensions of Algorithmic Thinking has recently been published by Bristol University Press. In 1956, during a year-long trip to London and in his early 20s, the mathematician and ...

“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...