《科学大讲堂 第244期》汤涛 院士：偏微分方程数值解：深度学习方法的机遇与挑战

以下内容根据公开信息整理，并经大模型处理生成，可能存在疏漏或误差，请以实际信息为准。

• 题目: 偏微分方程数值解：深度学习方法的机遇与挑战
• 主讲人：汤涛 院士 @ 广州南方学院
• 时间：2026年6月5日 15:00-16:00
• 地点：理学院一楼1142报告厅

主讲人简介

Professor Tao Tang is an Academician of the Chinese Academy of Sciences, an Academician of Academia Europaea, and an Academician of The World Academy of Sciences (TWAS). He is currently the President of Guangzhou Nanfang University and Vice President of the Chinese Mathematical Society. Professor Tang's main research interests lie in computational mathematics. His work on high-accuracy algorithms for partial differential equations and computational fluid dynamics has had a profound international impact. He was an invited 45-minute speaker at the International Congress of Mathematicians (ICM) and was elected a Fellow of the Society for Industrial and Applied Mathematics (SIAM) in 2012. Professor Tang has received numerous prestigious awards, including the Leslie Fox Prize in Numerical Analysis, the Feng Kang Prize for Scientific Computing, the Natural Science Award of the Ministry of Education of China, and the National Natural Science Award of China.

讲座简介

Deep learning has recently emerged as a prominent approach for numerically solving partial differential equations. This report will discuss several key challenges in deep learning-based PDE methods, including boundary condition handling, spatial-temporal sampling strategies, and high-dimensional non-convex optimization. It will also explore the feasibility of applying deep learning to operator learning and uncertainty quantification research, and summarize recent advances in this rapidly evolving field.

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