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 ...
AI methods are increasingly being used to improve grid reliability. Physics-informed neural networks are highlighted as a ...
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 ...
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 ...
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/ -- ...
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, ...
A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Previously met with skepticism, AI won scientists a Nobel Prize for Chemistry in 2024 after they used it to solve the protein folding and design problem, and it has now been adopted by biologists ...
Neural Concept aims to accelerate these timelines by integrating AI directly into CAD and physics-based simulation ...
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