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 ...

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 ...

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 ...

“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 ...

Imagine watching a conversation between brain cells, seeing chemical messages pass from one neuron to another. Scientists can ...

Confused about cost functions in neural networks? In this video, we break down what cost functions are, why they matter, and ...