论文题目：Label-Noise Robust Generative Adversarial Networks
论文地址：Label-Noise_Robust_Generative_Adversarial_Networks_CVPR_2019
作者博客：https://takuhirok.github.io/rGAN/
开源代码：https://github.com/takuhirok/rGAN/
we propose a novel family of GANs called label-noise robust GANs (rGANs), which, by incorporating a noise transition model, can learn a clean label conditional generative distribution even when training labels are noisy.
这里只简单记录作者的核心思想，如果后面的研究需要借鉴，将会更新此篇文章。
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本文标题：[论文]Label-Noise Robust Generativ
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