Hybrid climate modeling has emerged as an effective way to reduce the computational costs associated with cloud-resolving models while retaining their accuracy. The approach retains physics-based ...
4don MSN
Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures
Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular ...
The original version of this story appeared in Quanta Magazine. When she was 10 years old, Rose Yu got a birthday present that would change her life—and, potentially, the way we study physics. Her ...
Researchers present a comprehensive review of frontier AI applications in computational structural analysis from 2020 to 2025, focusing on graph neural networks (GNNs), sequence-to-sequence (Seq2Seq) ...
Methodology of the CondensNet model. CondensNet is a physically constrained DL parametrisation coupled with a climate dynamics engine to support hybrid modelling. The network architecture mainly has ...
Wildfires do not grow in a straight line. They begin as tiny, ...
A physicist has mounted one of the most detailed technical challenges yet against the idea that our universe is a computer simulation, arguing that the energy required to run such a program would ...
Artificial intelligence (AI) is increasingly prevalent, integrated into phone apps, search engines and social media platforms as well as supporting myriad research applications. Of particular interest ...
During surgery to correct an abnormal heartbeat, doctors rely on a mix of imaging and inference. Still, many critical details remain hidden. At RIT, artificial intelligence (AI) researchers want to ...
A milestone in biology has been achieved thanks to artificial intelligence (AI) machine learning and applied physics. A new peer-reviewed study by researchers affiliated with Harvard John A. Paulson ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results