Year: 2022
CAM-Net Digest, Vol. 19 (2022), Iss. 14 : p. 7
Abstract
课程日期：2022年8月16日-30日
授课时间：09:00-11:00
课时数：2课时/天，共30课时
ZOOMID：202 216 6027 密码：Zoom2022
授课老师：Prof. Haizhao Yang （University of Maryland,CollegePark）
主办单位：国家天元数学中部中心、湖北国家应用数学中心、武汉大学数学与统计学院
课程信息：
Description:
Part I: deep learning basics: feed-forward networks; recurrent neural networks; deep reinforcement learning;
Part II: deep learning applications: data-driven recovery of equations; data-driven prediction; solving partial differential equations; inverse problems, operator learning;
Part III: deep learning theory: approximation theory, optimization theory, and generalization theory of deep learning.
Important prerequisites:
Students must review basic numerical linear algebra, differential equations, probability, and optimization by themselves.
Approximate Schedule:
Each lecture is approximately one hour.
Lecture 1: Basic Machine Learning and Feed-forward Networks;
Lecture 2: Recurrent Neural Networks;
Lecture 3 and 4: Deep Reinforcement Learning;
Lecture 5: Data-driven Recovery of Equations;
Lecture 6: Data-driven Prediction;
Lecture 7 and 8: Solving Partial Differential Equations;
Lecture 9: Inverse Problems;
Lecture 10: Operator Learning;
Lecture 11 and 12: Deep Network Approximation;
Lecture 13 and 14: Deep Learning Optimization;
Lecture 15 and 16: Deep Learning Generalization.
【报名流程及联系人】
1、点击此处提交报名申请
2、请报名的同学加入qq群：743690605（仅用于本次课程通知发布、资料分享）；
3、报名截止日期为2022年08月14日
联系人：杨老师 电话：027-68788932 Email: tmcc@whu.edu.cn
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Journal Article Details
Publisher Name: Global Science Press
Language: Multiple languages
DOI: https://doi.org/2022-CAM-20834
CAM-Net Digest, Vol. 19 (2022), Iss. 14 : p. 7
Published online: 2022-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 1