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The Application of Machine Learning Methods to the Solution of Partial Differential Equations
The Application of Machine Learning Methods to the Solution of Partial Differential Equations
This course reviews the publications of the recent decade on using machine learning methods in solving partial differential equations, such as Physics Informed Neural Network (PINN). The course will include the materials on direct method, inverse method, reduced order modeling, and the assimilation of various types of observational data.
Lecturer
Date
17th March ~ 7th July, 2022
Website
Prerequisite
Basic knowledge on numerical methods for partial differential equations and neural network methods
Video Public
No
Notes Public
No
Lecturer Intro
Dr. Zhang received his bachelor's, master's, and doctor's degrees from Zhejiang University, Peking University, and Massachusetts Institute of Technology. He is currently a professor at the Beijing Institute of Mathematical Sciences and Applications, in the artificial intelligence and machine learning research group. He is currently interested in developing machine learning algorithms driven by both data and existing domain knowledge, and applying them to the interpretation and quantification of various physical, biological and social phenomena.