A Short Tutorial on Convolutional Neural Networks and Recurrent Neural Networks--Institute of Theoretical Physics，Chinese Academy of Sciences

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A Short Tutorial on Convolutional Neural Networks and Recurrent Neural Networks

06/03 2019

Title A Short Tutorial on Convolutional Neural Networks and Recurrent Neural Networks
Speaker
Date
Venue

Abstract

CAS Key Laboratory of Theoretical Physics

Institute of Theoretical Physics

Chinese Academy of Sciences

Seminar

Title

题目

A Short Tutorial on Convolutional Neural Networks and Recurrent Neural Networks

Speaker

报告人

朱占星

Affiliation

所在单位

北京大学数学科学学院

Date

日期

2019年6月3日（周一）上午9：00

Venue

地点

6420 ITP South Building

Abstract

摘要

In this tutorial, I will elaborate two powerful deep learning models, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), particularly suitable for modeling image and sequence data, respectively. I will introduce their architectures, the design principle and difficulties of training. Some variants will be introduced, such as ResNet, DenseNet, Long-Short Memory Network (LSTM), attention mechanism, etc. Various examples will be provided and analyzed as well.

Contact Person

所内联系人

Pan Zhang