东南大学闫亮副教授力智讲坛报告通知(2023-33)

报告题目：Failure-informed adaptive sampling for PINNs

报告时间：2023年8月2日（周三）9:30（北京时间）

报告地点：河海大学江宁校区乐学楼1030

报 告 人：闫亮副教授，东南大学

主办单位：江苏省力学学会信息化工作委员会

                 云顶yd2222咋登录不了

                 河海大学人工智能与自动化学院

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报告摘要：

Physics-informed neural networks (PINNs) have emerged as an effective technique for solving PDEs in a wide range of domains. Recent research has demonstrated, however, that the performance of PINNs can vary dramatically with different sampling procedures, and that using a fixed set of training points can be detrimental to the convergence of PINNs to the correct solution. In this talk, we present an adaptive approach termed failure-informed PINNs(FI-PINNs), which is inspired by the viewpoint of reliability analysis. The basic idea is to define a failure probability by using the residual, which represents the reliability of the PINNs. With the aim of placing more samples in the failure region and fewer samples in the safe region, FI-PINNs employs a failure-informed enrichment technique to incrementally add new collocation points to the training set adaptively. When compared to the conventional PINNs method and the residual-based adaptive refinement method, the developed algorithm can significantly improve accuracy, especially for low regularity and high-dimensional problems.

报告人简介：

闫亮，副教授、博士生导师。主要从事不确定性量化、贝叶斯建模与计算以及科学机器学习方法的研究。2017年入选江苏省高校“青蓝工程”优秀青年骨干教师培养对象，2018年入选东南大学首批“至善青年学者”（A层次）支持计划。2019年在第十一届反问题年会上获得“优秀青年学术奖”。作为负责人获得三项国家自然科学基金和一项江苏省自然科学基金，在《SIAM J. Sci. Comput.》、《Inverse Problems》、《J. Comput. Phys.》等国内外刊物上发表30多篇学术论文。