Letian YI, Siyuan YANG, Ying CUI, and Zhilu LAI (2025). Transforming Physics-Informed Machine Learning to Convex Optimization. Physics-Informed Machine Learning (PIML) offers a powerful paradigm of ...

A physics-aware reasoning server that learns from books, stores equations as memory, and solves problems by predicting and applying the right formulas—like an LLM, but with logic. The MCP (Model ...

Google updated its search engine and Lens tool with new features to help you visualize and solve problems in more difficult subjects like geometry, physics, trigonometry and calculus. The update ...

Abstract: This work extends Extreme Learning Machines (ELM) to obtain solutions for nonlinear higher order partial differential equations that govern the physics of different domains. The ELM operates ...

This is a preview. Log in through your library . Abstract We illustrate a general method, which is useful for the solution of integro-differential equations, and apply the technique to solve the ...

We present a new, unified approach to the solution of the elastance problem in electrostatics and the mobility problem in Stokes flow. More precisely, we construct integral representations that lead ...

One of the most stubborn problems in physics today is the fact that our two best theories to explain the Universe - general relativity and quantum mechanics - function perfectly well on their own, but ...