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彭伟 助理研究员:IDRLnet: A Physics-Informed Neural Network Library

本站小编 Free考研考试/2021-12-26


Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars
Speaker: 彭伟 助理研究员,军事科学院国防科技创新研究院
Inviter: 优化与应用研究中心
Title:
 IDRLnet: A Physics-Informed Neural Network Library
Time & Venue:
 2021.11.05 09:30-10:30 腾讯会议ID：158 245 214
Abstract:
 Physics Informed Neural Network (PINN) is a scientific computing framework used to solve both forward and inverse problems modeled by Partial Differential Equations (PDEs). This paper introduces 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, artificial 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.

相关话题/优化 创新 军事科学院 腾讯 国防科技

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