f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization 论文笔记
文章目录 摘要 介绍 方法 f-divergence族 f-divergence的变分估计 变分散度最小化 算法流程 实用建议 摘要 将GAN推广到variational divergence estimation. 讨论不同的f-divergence下如何实现. 介绍 GAN可以看作优化JS距离, JS距离无法直接优化, 可以通过判别器, 近似JS距离. 可以将JS距离推广到一般的f-diver
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相关文章
- 1. 【f-GAN】f-GAN：Training Generative Neural Samplers using Variational Divergence Minimization
- 2. GAN 论文大汇总
- 3. Neural Generative Question Answering笔记
- 4. 论文笔记:Bag of Freebies for Training Object Detection Neural Networks
- 5. 【论文笔记】HSIC WIth Small Training Sample Size Using Superpixel-Guided Training Sample Enlargement
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- 7. Singing-Voice Separation from Monaural Recordings using Deep Recurrent Neural Networks论文笔记
- 8. 【论文笔记】Improving Language Understanding by Generative Pre-Training
- 9. 【DL笔记】Tutorial on Variational AutoEncoder——中英文对照（更新中）
- 10. Generative Adversarial Nets论文笔记