讲座论坛
荔园数学讲坛: Some numerical issues regarding deep neural network approximations for PDEs
发布时间:2022-07-27 12:46:34 3524

内容摘要: 

Deep neural networks have been widely used for solving PDEs in recently years. In this talk, we shall discuss some numerical issues for such approaches. In particular, we shall present some recent ideas for dealing with essential boundary conditions, nonlocal operators and effective sampling strategies on unbounded domains.

主讲人简介: 

周涛,中国科学院数学与系统科学研究院研究员。曾于瑞士洛桑联邦理工大学从事博士后研究。主要研究方向为不确定性量化、随机最优控制以及时间并行算法等。在国际权威期刊如SIAM Review、SINUM、JCP等发表论文60余篇。2018年获自然科学基金委“优秀青年科学基金”资助。现担任SIAM J Sci Comput、Commun. Comput. Phys、J Sci Comput等国际期刊编委,国际不确定性量化期刊(International Journal for UQ)副主编。