This repository allows you to solve forward and inverse problems related to partial differential equations (PDEs) using finite basis physics-informed neural networks (FBPINNs). To improve the ...
Find out what happened to NASA’s Katherine Johnson, Mary Jackson and Dorothy Vaughan, a.k.a. the real women behind ‘Hidden ...
A Mathematician with early access to XAI Grok 4.20, found a new Bellman function for one of the problems he had been working ...
Abstract: Nonlinear equation systems are ubiquitous in a variety of fields, and how to tackle them has drawn much attention, especially dynamic ones. As a particular class of recurrent neural network, ...
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 ...
Our teacher already knows there is a positive relationship between how much time was spent on an essay and the grade the essay gets, but we’re going to need some data to demonstrate this properly.
Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...
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