In this course, we will cover some of the fundamental elements in deep learning and some
topics related to using Deep Learning to advance Scientific Computings. This course will
review some topics in numerical analysis, linear algebra, and differential equations, and move
forward to introduce the latest architecture in deep learning, for instance, the PINNs, Neural
ODE, Fourier Neural Operator, and ONet.
在本課程中，我們將涵蓋深度學習的一些基本要素，以及一些與利用深度學習來推進科學計
算相關的主題。本課程將回顧數值分析、線性代數和微分方程的一些主題，並進一步介紹深
度學習的最新架構，例如 PINN、神經微分方程 (ODE)、傅立葉神經算子和 ONet。