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 ...

Learn about the most prominent types of modern neural networks such as feedforward, recurrent, convolutional, and transformer networks, and their use cases in modern AI. Neural networks are the ...

How do the circuits of the human brain work—and what happens when they are disrupted? To investigate these questions, ...

An international collaboration has resulted in a paper in Scientific Reports. Associate Professor Timur Madzhidov, one of the co-authors of the publication, explains, "First, we fed existing chemical ...

Suppose you have a thousand-page book, but each page has only a single line of text. You’re supposed to extract the information contained in the book using a scanner, only this particular scanner ...

Using single-cell RNA sequencing and genetic screening, the researchers identified key surface proteins that mediate ...

An MIT spinoff co-founded by robotics luminary Daniela Rus aims to build general-purpose AI systems powered by a relatively new type of AI model called a liquid neural network. The spinoff, aptly ...

Ryan Lee has received funding from the Air Force Office of Science Research . The new material is a type of architected material, which gets its properties mainly from the geometry and specific traits ...