BEGAN: Boundary Equilibrium Generative Adversarial Networks阅读笔记
BEGAN: Boundary Equilibrium Generative Adversarial Networks阅读笔记 摘要 我们提出了一种新的用于促成训练时生成器和判别器实现均衡（Equilibrium）的方法，以及一个配套的 loss，这个 loss 由 Wasserstein distance 衍生而来，Wasserstein distance 则是训练基于自编码器的生成对抗网络（G
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相关文章
- 1. Generative Adversarial Nets[BEGAN]
- 2. 【阅读笔记】Generative Adversarial Nets
- 3. Generative Adversarial Networks: An Overview文献阅读笔记
- 4. Conditional Generative Adversarial Networks（CGAN）笔记
- 5. Generating Adversarial Examples with Adversarial Networks阅读笔记
- 6. BEGAN论文阅读
- 7. Generative Adversarial Nets (GAN) 阅读笔记
- 8. Generative Adversarial Nets 论文阅读笔记
- 9. Generating Multi-label Discrete Electronic Health Records using Generative Adversarial Networks阅读笔记
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