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 ...

Shifting focus on a visual scene without moving our eyes—think driving, or reading a room for the reaction to your joke—is a ...

A Japanese research team has successfully reproduced the human neural circuit in vitro using multi-region miniature organs ...

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 ...

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 ...

The team proposed propose a novel entity-type-enriched cascaded neural network (E 2 CNN) that considers the overlap triple problem and entity-type information to construct a Chinese financial ...

The German sensor-maker Leuze claims that it has been able to cut measurement errors in demanding industrial applications by ...

The term generative AI refers to a relatively new field of AI that can create human-like content, from pictures and videos to poetry and even computer code. To achieve this, several different ...