Tag: physics-informed machine learning

Researchers in Zhengzhou have built a graph neural network that encodes the measured noise of superconducting quantum processors to correct ...

Researchers in China have built a physics-guided deep learning model that improves groundwater-level prediction in heavily pumped agricultural aquifers by ...

Researchers have developed a physics-informed, uncertainty-aware graph neural network that predicts jet engine remaining useful life with record robustness under ...

Researchers have developed a physics-informed machine learning framework that predicts the remaining useful life of electric vehicle drive systems with ...

Researchers have developed a physics-guided machine learning framework that turns Slope Stability Radar data into regime-based early warnings of rock ...

Researchers have developed a physics-informed neural network with an attention mechanism that predicts electric vehicle range with far greater accuracy ...

Tohoku University researchers propose a framework called Physics-Grounded Materials AI that embeds thermodynamic, kinetic, and electronic-structure principles into machine learning ...

Researchers have developed a physics-aware graph neural network that detects power grid anomalies hidden by manipulated measurements and deceptive network ...

Researchers in China have developed a physics-transfer learning framework that embeds elastic mechanics into neural networks to predict how the ...

USC has been selected as one of the first institutions to help lead the U.S. Department of Energy’s Genesis Mission, ...