Machine Learning for Solving PDEs: Random Feature Method

This lecture explores the Random Feature Method for solving PDEs, showcasing how machine learning algorithms can efficiently approximate high-dimensional functions. It delves into the applications of machine learning in image classification, generating fake human faces, and playing games like Go. The lecture also discusses the challenges of traditional algorithms in high-dimensional problems and the advantages of neural networks in approximating functions. Furthermore, it covers the use of deep learning in scientific computing, stochastic control, and multi-scale modeling, emphasizing the potential of machine learning in revolutionizing various scientific fields.