玻尔兹曼机
深信不疑网络
深度学习
自编码
计算机科学
生成语法
人工智能
生成模型
限制玻尔兹曼机
机器学习
人工神经网络
作者
Xu Jin,Hui Li,Shilong Zhou
标识
DOI:10.1080/02564602.2014.987328
摘要
As an important category of deep models, deep generative model has attracted more and more attention with the proposal of Deep Belief Networks (DBNs) and the fast greedy training algorithm based on restricted Boltzmann machines (RBMs). In the past few years, many different deep generative models are proposed and used in the area of Artificial Intelligence. In this paper, three important deep generative models including DBNs, deep autoencoder, and deep Boltzmann machine are reviewed. In addition, some successful applications of deep generative models in image processing, speech recognition and information retrieval are also introduced and analysed.
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