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 ...

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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 ...

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The initial research papers date back to 2018, but for most, the notion of liquid networks (or liquid neural networks) is a new one. It was “Liquid Time-constant Networks,” published at the tail end ...

Scientists propose a new way of implementing a neural network with an optical system which could make machine learning more sustainable in the future. The researchers at the Max Planck Institute for ...

DLSS 5 isn't just smarter upscaling. Nvidia's new neural renderer understands what's in the scene — and re-lights it. Here's ...

Researchers have developed photonic computing chips that overcome key limitations for a type of neural network known as a photonic spiking neural system. By enabling fast learning and decision making ...