We use this handy neural mechanism to learn, remember, solve problems and generally navigate our reality. “It’s a network effect,” said UC Santa Barbara mechanical engineering professor Francesco ...

and reveals a novel neural-glia-fibroblast-lymphatic regulatory axis. This provides a new framework for understanding how the brain adapts its lymphatic network based on functional needs ...

But as mobile hardware advances, Machine Learning (ML) techniques, particularly Graph Neural Networks (GNNs), are emerging as a powerful, efficient alternative to emulate physics on mobile. GNNs are ...

It's an AI-based upscaling solution that utilizes Recurrent Neural Networks (RNN), but to enable PSSR, Sony first had to create what it calls a "fully fused network." Okay, so let's go over what ...

“When we scale them up to larger data sets, nothing can compete.” And yet, all this time, neural networks have had a disadvantage. The basic building block of many of today’s successful networks is ...

Neural Texture Block Compression" @ #EGSR2024 in London. Nobody likes downloading huge game packages. Our method compresses the texture using a neural network, reducing data size. Unchanged ...

OpenAI, the headline-making humans responsible for ChatGPT's rise and a lot of chatter about LLMs (large language models), unveiled their latest creation, Microscope, a nifty neural visualization ...

A technical paper titled “Accelerating Defect Predictions in Semiconductors Using Graph Neural Networks” was published by researchers at Purdue University, Indian Institute of Technology (IIT) Madras, ...

Neural networks are therefore a specialized kind of directed graph. Many neural networks distinguish between three layers of nodes: input, hidden, and output. The input layer has neurons that ...