Improving GAN training with probability ratio clipping and sample reweighting

Despite success on a wide range of problems related to vision, generative adversarial networks (GANs) often suffer from inferior performance due to unstable training, especially for text generation. To solve this issue, we propose a new variational GAN training framework which enjoys superior traini...

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Main Authors: WU, Yue, ZHOU, Pan, GORDON, Andrew Wilson, XING, Eric, HU, Zhiting
格式: text
語言:English
出版: Institutional Knowledge at Singapore Management University 2020
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在線閱讀:https://ink.library.smu.edu.sg/sis_research/8996
https://ink.library.smu.edu.sg/context/sis_research/article/9999/viewcontent/2020_NeurIPS_GAN.pdf
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