BIMSA > 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
Xiaoming Zhang
Date
17th March ~ 7th July, 2022
Prerequisite
Basic knowledge on numerical methods for partial differential equations and neural network methods
Video Public
No
Notes Public
No
Lecturer Intro
Dr. Zhang Xiaoming 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, responsible for the artificial intelligence and big data research team. Dr. Zhang has long been engaged in the research, development, and application of artificial intelligence technologies to big data prediction and resource optimization and allocations problems. He presided over the development of digital intelligence service platform "printing and dyeing brain", which was well recognized in the industry. At present, his work focuses on the mathematical problems in developing industrial digital twins.