Web: https://towardsdatascience.com/solving-differential-equations-with-neural-networks-afdcf7b8bcc4?source=rss----7f60cf5620c9---4

May 5, 2022, 6:12 a.m. | Mario Dagrada

Towards Data Science - Medium towardsdatascience.com

A hands-on introduction to physics-informed neural networks with PyTorch

Photo by Dawid Małecki on Unsplash

Over the last decades, artificial neural networks have been used to solve problems in varied applied domains such as computer vision, natural language processing and many more. Recently, another very promising application has emerged in the scientific machine learning (ML) community: The solution of partial differential equations (PDEs) using artificial neural networks, using an approach normally referred to as physics-informed neural networks (PINNs). Today, PINNs …

differential-equations machine learning networks neural neural networks physics pytorch

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California