This cross-journal Collection between Nature Communications, Nature Computational Science, Communications Physics, and Scientific Reports brings together the advances in Physics-Informed Machine ...

More information: Reconstruction of tropical cyclone boundary layer wind field using physics-informed machine learning, Physics of Fluids (2024). DOI: 10.1063/5.0234728.

Improving hurricane modeling with physics-informed machine learning Algorithm reconstructs wind fields quickly, accurately, and with less observational data.

Scientists know this and have devised several ways to account for the atmosphere’s corrupting influence on remote sensing data. “This problem is as old as overhead imagery,” said James Koch, a data ...

Organic photovoltaics max out at 15%-20% efficiency. Lehigh University researchers are using physics-informed machine learning to improve this efficiency. Their findings suggest a machine learning ...

To address this, the research group used a "physics-informed" machine learning approach to infer these disorder characteristics indirectly.

The Kennedy College of Science, Department of Physics & Applied Physics, invites you to attend a doctoral thesis defense by Abantika Ghosh on "Physics-Informed Machine Learning for Optical ...

Machine learning can get a boost from quantum physics. On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in ...

Improving hurricane modeling with physics-informed machine learning. ScienceDaily . Retrieved June 11, 2025 from www.sciencedaily.com / releases / 2024 / 11 / 241119132424.htm ...