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Numerical methods for engineering, uncertainty quantification and machine learning
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Leader of Teaching Group:Peng WANG

Members of Teaching Group:Peng WANG, Wei XING

Course Introduction:数值方法广泛应用于微电子科学与工程应用。无论是探究自旋电子在电磁场中运动的Landau-Liftshitz-Gilbert随机方程,还是仿真集成电路中的节点电流守恒方程,都需要数值算法的帮助。 本门课程旨在通过面授、作业、编程大作业和考试四种形式,向工程领域的研究生讲授基础数值方法、常用不确定性量化方法和热门机器学习算法。具体内容包含了优化、基础矩阵理论、数值积分、常微分方程和偏微分方程的数值解、随机计算、逆问题、并行计算、贝叶斯统计模型、高斯过程和深度神经网络。

Venue:学院路校区

Schedule:周二、周五 第6、7节

Target Students:Graduate

Discipline:Mathematics

Teacher:Peng WANG, Wei XING

Class classroom:4-315

School Year:2020-2021

Semester:Autumn Term

Course number:41112101

Course Type:Postgraduate Course:

Top-Quality Courses or Not:no

Courses and reference books:Numerical methods for engineers, Steven Chapra, Raymond Canale; 不确定性量化,王鹏、修东滨; Pattern Recognition and Machine Learning, Christopher Bishop;

Personal information

Professor
Supervisor of Doctorate Candidates
Supervisor of Master's Candidates

E-Mail:

Date of Employment:2014-02-01

School/Department:School of Microelectronics

Education Level:博士研究生

Gender:Male

Contact Information:wang DOT peng AT BUAA DOT EDU DOT CN

Degree:博士

Status:Employed

Alma Mater:University of California, San Diego

Discipline:Electronic Science and Technology
Mathematics

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