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CBMS Conference: Deep Learning and Numerical Partial Differential Equations

CBMS 会议：深度学习和数值偏微分方程

基本信息

批准号：
2228010
负责人：
Mingchao Cai
金额：
$ 3.5万
依托单位：
Morgan State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2023
资助国家：
美国
起止时间：
2023-03-01 至 2024-02-29
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2228010&HistoricalAwards=false
关键词：
CBMS Conference Deep Learning Numerical

项目摘要

This award provides support for the Conference Board of the Mathematical Sciences conference "Deep Learning and Numerical PDEs," to be held at Morgan State University in Baltimore, June 19-24, 2023. This conference will bring together experts from mathematics, computer science, and engineering on topics involving deep learning and numerical partial differential equations (PDEs). As such, it will provide an education platform and forum for experts and young researchers to communicate new advancements in theoretical and application developments. The interaction between theory and application experts is intended to spark new ideas and collaborative projects. The conference will fund approximately 30 participants, especially graduate students, postdoctoral associates, early-career researchers, and individuals from underrepresented groups. The meeting aims to provide extraordinary opportunities to the participants to study the fundamental mathematical theory of deep learning, communicate potential important research directions, discuss possible practical applications, and interact with leading researchers. The distinguished principal lecturer will be Verne M. Willaman Professor Jinchao Xu of Pennsylvania State University. The lectures will present the latest developments on the theory and applications of deep learning, bridging models and algorithms from two different fields: (1) machine learning, including logistic regression and deep neural networks, and (2) numerical PDEs, including finite element and multigrid methods. The lecture series builds upon a discussion on the latest developments in machine learning models and algorithms and presents cutting-edge research on intrinsically connected topics to the participants of the conference. As a result, this conference is expected to bring novel insights into the understanding of deep learning, and to further promote their analysis and applications in different scientific and engineering fields. For more information, please refer to the conference webpage: https://sites.google.com/view/nsf-cbms-dl-nmpde/homeThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该奖项为将于2023年6月19日至24日在巴尔的摩的摩根州立大学举行的数学科学会议“深度学习和数值偏微分方程”会议委员会提供支持。本次会议将汇集来自数学、计算机科学和工程领域的专家，主题涉及深度学习和数值偏微分方程（PDE）。因此，它将为专家和年轻研究人员提供一个教育平台和论坛，以交流理论和应用发展的新进展。理论和应用专家之间的互动旨在激发新的想法和合作项目。会议将资助大约30名参与者，特别是研究生，博士后，早期职业研究人员和来自代表性不足群体的个人。会议旨在为与会者提供非凡的机会，学习深度学习的基础数学理论，交流潜在的重要研究方向，讨论可能的实际应用，并与领先的研究人员进行互动。杰出的首席讲师将是凡尔纳M。宾夕法尼亚州立大学教授徐金超。讲座将介绍深度学习理论和应用的最新发展，桥接两个不同领域的模型和算法：（1）机器学习，包括逻辑回归和深度神经网络，以及（2）数值偏微分方程，包括有限元和多重网格方法。该系列讲座建立在对机器学习模型和算法最新发展的讨论基础上，并向会议参与者展示了关于内在联系主题的前沿研究。因此，本次会议有望为深度学习的理解带来新的见解，并进一步促进其在不同科学和工程领域的分析和应用。欲了解更多信息，请参阅会议网页：https://sites.google.com/view/nsf-cbms-dl-nmpde/homeThis奖反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。