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IDRLnet: A Physics-Informed Neural Network Library
【2022.7.7 7:00pm, 腾讯会议】

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 2022-6-28

  Colloquia & Seminars 

  Speaker

周炜恩助理研究员,国防科技创新研究院

  Title

IDRLnet: A Physics-Informed Neural Network Library

  Time

2022.07.07 19:00-20:00

  Venue

腾讯会议ID:129-814-616

  Abstract

Physics Informed Neural Network (PINN) is a scienti?c computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs). We propose IDRLnet, a Python toolbox for modeling and solving problems through PINN systematically. IDRLnet constructs the framework for a wide range of PINN algorithms and applications. It provides a structured way to incorporate geometric objects, data sources, arti?cial neural networks, loss metrics, and optimizers within Python. Furthermore, it provides functionality to solve noisy inverse problems, variational minimization, and integral differential equations. New PINN variants can be integrated into the framework easily. Source code, tutorials, and documentation are available at https://github.com/idrl-lab/idrlnet.

  Affiliation

 

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