The difference learning of hidden layer between autoencoder and variational autoencoder
The difference learning of hidden layer between autoencoder and variational autoencoder
复制标题
DOI：
10.1109/ccdc.2017.7979344
复制
发表时间：
2017-05
期刊：
影响因子：
--
通讯作者：
Qingyang Xu;Zhe Wu;Yiqin Yang;Li Zhang
中科院分区：
文献类型：
--
作者：
Qingyang Xu;Zhe Wu;Yiqin Yang;Li Zhang
Autoencoder是一种优秀的无监督学习算法。但在解码过程中不能产生多种采样数据。变分自编码器是一种典型的生成式对抗网络，它可以生成各种数据来扩充样本数据。本文主要对隐层信息学习进行研究。在仿真中，我们比较了传统自编码器和变分自编码器的隐层学习。
Autoencoder is an excellent unsupervised learning algorithm. However, it can not generate kinds of sample data in the decoding process. Variational autoencoder is a typical generative adversarial net which can generate various data to augment the sample data. In this paper, we want to do some research about the information learning in hidden layer. In the simulation, we compare the hidden layer learning of hidden layer in conventional autoencoder and variational autoencoder.