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 ...
It’s been ten years since AlexNet, a deep learning convolutional neural network (CNN) model running on GPUs, displaced more traditional vision processing algorithms to win the ImageNet Large Scale ...
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Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability
AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
The German sensor-maker Leuze claims that it has been able to cut measurement errors in demanding industrial applications by ...
Emergence of new applications and use cases: Neural networks are being applied to an increasingly diverse range of applications, including computer vision, natural language processing, fraud detection ...
Researchers have developed a fiber neural network system that performs intelligent processing of optical communication signals directly in the light domain. This approach integrates optical ...
“Neural networks are currently the most powerful tools in artificial intelligence,” said Sebastian Wetzel, a researcher at the Perimeter Institute for Theoretical Physics. “When we scale them up to ...
MicroCloud Hologram Inc. (NASDAQ: HOLO), ("HOLO" or the "Company"), a technology service provider, innovatively launches a quantum-enhanced deep convolutional neural network image 3D reconstruction ...
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