Dylan Kane likes his math curriculum. But there’s one important piece missing, he says. The 7th grade math teacher in Leadville, Colo., uses a program that teaches math skills through real-world ...
More than 20% of the workload on the world's 500 fastest supercomputers is spent simulating how atoms and molecules move—with applications ranging from material design to identifying drug interactions ...
Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...
In mid-May, OpenAI announced that an internal AI model had disproved the Erdős unit distance conjecture, a famous problem in discrete geometry that had stumped human mathematicians for the last 80 ...
Physics-aware machine learning integrates domain-specific physical knowledge into machine learning models, leading to the development of physics-informed neural networks (PINNs). PINNs embed physical ...
Nearly 200 years ago, the physicists Claude-Louis Navier and George Gabriel Stokes put the finishing touches on a set of equations that describe how fluids swirl. And for nearly 200 years, the ...
Abstract: This paper introduces Physics-Informed Deep Equilibrium Models (PIDEQs) for solving initial value problems (IVPs) of ordinary differential equations (ODEs). Leveraging recent advancements in ...
Engineers design safer cars, more resilient spacecraft, and stronger bridges using complex math problems that drive the underlying processes. Similarly, doctors use mathematical models to predict ...
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