Machine learning models are designed to take in data, to find patterns or relationships within those data, and to use what ...

Physics-informed neural networks (PINNs) represent a burgeoning paradigm in computational science, whereby deep learning frameworks are augmented with explicit physical laws to solve both forward and ...

Using artificial intelligence, physicists have compressed a daunting quantum problem that until now required 100,000 equations into a bite-size task of as few as four equations — all without ...

Differential equations are fundamental tools in physics: they are used to describe phenomena ranging from fluid dynamics to general relativity. But when these equations become stiff (i.e. they involve ...

A machine learning model used neural decoding to show how we think about abstract concepts like electrical current and diffraction. The results could change how we teach physics. Share on Facebook ...

Clausell Mathis receives funding from U.S. Department of Education as a Co-PI on the Education Innovation and Research Grant program. . America has a physics problem. Research shows that access to ...