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 ...

Training deep neural networks like Transformers is challenging. They suffering from vanishing gradients, ineffective weight ...

During my first semester as a computer science graduate student at Princeton, I took COS 402: Artificial Intelligence. Toward the end of the semester, there was a lecture about neural networks. This ...

Nextchip license NeuPro-M NPU to bring powerful and highly efficient AI capabilities to boost performance and capabilities of automotive safety systems ROCKVILLE, Md., April 22, 2025 /PRNewswire/ -- ...

Researchers from the University of Tokyo in collaboration with Aisin Corporation have demonstrated that universal scaling laws, which describe how the properties of a system change with size and scale ...

As the world grapples with the energy crisis and environmental concerns, the focus on renewable energy sources has intensified. Lithium-ion batteries, with their high energy density and low pollution, ...

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.

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