Over the past decades, neural networks and optimisation techniques have evolved into critical tools for tackling complex, time-varying problems in engineering and the physical sciences. Neural ...

A new study suggests that the brain processes information with high efficiency by synchronizing the physical wiring of neural ...

MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, released learnable quantum spectral filter technology for hybrid graph neural networks. This ...

Neural network pruning is a key technique for deploying artificial intelligence (AI) models based on deep neural networks (DNNs) on resource-constrained platforms, such as mobile devices. However, ...

Artificial intelligence (AI) is increasingly transforming computational mechanics, yet many AI-driven models remain limited by poor interpretability, weak generalization, and insufficient physical ...

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 ...

For all their brilliance, artificial neural networks remain as inscrutable as ever. As these networks get bigger, their abilities explode, but deciphering their inner workings has always been near ...

AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...

Your grade school teacher probably didn’t show you how to add 20-digit numbers. But if you know how to add smaller numbers, all you need is paper and pencil and a bit of patience. Start with the ones ...