自动化学报2018，Vol.44Issue(5)：775-792,18.DOI:10.16383/j.aas.2018.y000002
人工智能研究的新前线:生成式对抗网络
The New Frontier of AI Research: Generative Adversarial Networks
摘要
Abstract
Recently, generative adversarial networks (GAN) have become one of the most popular topics in artificial intelligent field. Its outstanding capability of generating realistic samples not only revived the research of generative model, but also inspired the research of semi-supervised learning and unsupervised learning. In this paper, we introduce the basic idea of GAN, and comb its recent development in theory and practice. By concluding its improvements of network structures, optimization methods, the form of the game, the ensemble methods, and its applications, we found the inner logic of its development.关键词
深度学习/生成式对抗网络/生成模型/对抗学习/平行学习Key words
Deep learning/generative adversarial networks/generative model/adversarial learning/parallel learning引用本文复制引用
林懿伦,戴星原,李力,王晓,王飞跃..人工智能研究的新前线:生成式对抗网络[J].自动化学报,2018,44(5):775-792,18.基金项目
国家自然科学基金(61533019,61702519),北京市科技项目 Supported by National Natural Science Foundation of China(61533019, 61702519), Beijing Municipal Science and Technol-ogy Commission Program D17110600030000, ZC179074Z) (D17110600030000, ZC179074Z) 资助 （61533019,61702519）
