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

Submissions that provide evidence of scalable, robust, and reliable physics-informed machine learning approaches for large-scale, real-world applications are particularly welcome.

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

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 ...

In the world of particle physics, where scientists unravel the mysteries of the universe, artificial intelligence (AI) and machine learning (ML) are making waves with how they're increasing ...

Using a new physics-informed machine learning approach, researchers discovered two new high-entropy alloys with extremely low thermal expansion, a new study reports. The approach could represent a ...

To address this, the research group used a "physics-informed" machine learning approach to infer these disorder characteristics indirectly. This was based on how the internal disorder affected the ...

STOCKHOLM — John Hopfield and Geoffrey Hinton were awarded the Nobel Prize in physics Tuesday for discoveries and inventions that formed the building blocks of machine learning.

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