Speaker：Jingrun Chen（University of Science and Technology of China）

Time：2022-04-27, 16:30

Location：Tencent Meeting ID： 329822168（No Password）

Abstract:

Solving partial differential equations (PDEs) by deep neural networks has attracted significant attentions in recent years. In this presentation, I will discuss three pieces of works related to this topic from the perspective of classical numerical analysis: (1) solving high-order PDEs by designing a new model based on the mixed residual formulation; (2) capturing shock waves with random inputs by designing a new model based on the classical shock-capturing scheme; (3) constructing neural networks by using the low-rank structure explicitly. Numerical tests are provided to show the effectiveness of these ideas.