Generative Adversarial Nets
論文地址：https://arxiv.org/abs/1406.2661 GAN，顧名思義，生成對抗網絡。網絡由兩部分組成，generative model G 和 discriminative model D ，整個網絡的主要功能就是通過不斷迭代，使得G網絡的生成數據分佈趨近於真實數據分佈，最終達到D網絡的判別概率趨近1/2。 由上式可以看出，G和D的訓練其實就是關於函數V(D, G)的極小極大
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相關文章
- 1. Conditional Generative Adversarial Nets
- 2. Generative Adversarial Nets（譯）
- 3. paper：Conditional Generative Adversarial Nets
- 4. Generative Adversarial Nets[CycleGAN]
- 5. Generative Adversarial Nets
- 6. cGAN:Conditional Generative Adversarial Nets
- 7. Generative Adversarial Nets[pix2pix]
- 8. Generative Adversarial Nets (譯)
- 9. Generative Adversarial Nets[BEGAN]
- 10. Generative Adversarial Nets(GAN Tensorflow)