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Oct, 2018
关于生成对抗网络的自我调制
On Self Modulation for Generative Adversarial Networks
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Ting Chen, Mario Lucic, Neil Houlsby, Sylvain Gelly
TL;DR
本文提出了一种简单的结构性改进self-modulation,以提高生成对抗网络(GAN)的性能,并证明其可以适用于不同的数据集、架构、损失函数、正则化和超参数设置,大规模的实证研究表明,相对FID降低了5%~35%,并且在124/144的研究设置中提高了GAN的性能
Abstract
Training
generative adversarial networks
(GANs) is notoriously challenging. We propose and study an
architectural modification
,
self-modulation
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