An artificial neural network (ANN) is a type of machine learning that identifies patterns from data to make predictions about its features. Scientists like Grace Lindsay, computational neuroscientist ...

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 ...

Representation learning lies at the core of modern artificial intelligence, enabling neural networks to uncover meaningful, ...

The human brain, with its billions of interconnected neurons giving rise to consciousness, is generally considered the most powerful and flexible computer in the known universe. Yet for decades ...

The simplified approach makes it easier to see how neural networks produce the outputs they do. A tweak to the way artificial neurons work in neural networks could make AIs easier to decipher.

As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models ...

The TLE-PINN method integrates EPINN and deep learning models through a transfer learning framework, combining strong physical constraints and efficient computational capabilities to accurately ...

Rose Yu has a plan for how to make AI better, faster and smarter — and it’s already yielding results. When she was 10 years old, Rose Yu got a birthday present that would change her life — and, ...