[解讀] ClusterGAN : Latent Space Clustering in Generative Adversarial Networks
鏈接: https://arxiv.org/abs/1809.03627v2 ClusterGAN 是一個 GAN 的變體, 通過使得生成樣本反推的隱變量在隱空間中具有明顯的簇的特徵, 來提升 GAN 的性能. 相關工作 InfoGAN [4] 是一個研究在隱空間中進行可解釋性的表徵學習的開創新方法, 目標是創建可解釋性的和可解的隱變量. 雖然 InfoGAN 使用了離散的隱變量, 但它不是爲聚類
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相關文章
- 1. Graphical Generative Adversarial Networks
- 2. [解讀] Coupled Generative Adversarial Networks
- 3. Triangle Generative Adversarial Networks
- 4. Contrastive Generative Adversarial Networks
- 5. A wizard’s guide to Adversarial Autoencoders: Part 2, Exploring latent space with Adversarial Autoen
- 6. [Style Transfer]—Generative adversarial networks and adversarial method in biomedical image analysis
- 7. Self-Attention Generative Adversarial Networks 論文解讀
- 8. Generative Adversarial Networks: An Overview文獻閱讀筆記
- 9. [解讀] COEGAN Evaluating the Coevolution Effect in Generative Adversarial Networks
- 10. Generative Adversarial Networks overview（2）