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Title: NLP-Notes/DeepLearningAlgorithm/adversarial_training_study at main · feihong8743/NLP-Notes · GitHub

Open Graph Title: NLP-Notes/DeepLearningAlgorithm/adversarial_training_study at main · feihong8743/NLP-Notes

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Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - NLP-Notes/DeepLearningAlgorithm/adversarial_training_study at main · feihong8743/NLP-Notes

Open Graph Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - feihong8743/NLP-Notes

X Description: 本项目是作者们根据个人面试和经验总结出的自然语言处理(NLP)面试准备的学习笔记与资料，该资料目前包含 自然语言处理各领域的 面试题积累。 - feihong8743/NLP-Notes

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readme.mdhttps://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#readme
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#关于生成对抗网络gan那些你不知道的事
https://github.com/km1994/nlp_paper_studyhttps://github.com/km1994/nlp_paper_study
https://github.com/feihong8743/NLP-Notes/blob/main/DeepLearningAlgorithm/adversarial_training_study/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20210203235123.png
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#一动机
玻尔兹曼机(Boltzmann machine)https://note.wiz.cn/web?dc=677f1e8f-ec8c-43eb-b0dc-fd5a17721384&cmd=kw%2C&kb=cc2cc09f-709e-444d-ab2f-da6218b57dd2
生成对抗网络（Generative Adversarial Network，GAN）模型https://link.zhihu.com/?target=https%3A//arxiv.org/pdf/1406.2661.pdf
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#二介绍篇
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#21-gan-的基本思想
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#22-gan-基本介绍
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#221--gan-的基本结构
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#222-gan-的基本思想
https://github.com/feihong8743/NLP-Notes/blob/main/DeepLearningAlgorithm/adversarial_training_study/img/%E5%BE%AE%E4%BF%A1%E6%88%AA%E5%9B%BE_20200805232522.png
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#三训练篇
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#31-生成器介绍
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#32-判别器介绍
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#33-训练过程
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#34--训练所涉及相关理论基础
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#四总结
https://github.com/feihong8743/NLP-Notes/tree/main/DeepLearningAlgorithm/adversarial_training_study#参考资料
通俗理解生成对抗网络GANhttps://zhuanlan.zhihu.com/p/33752313
白话生成对抗网络 GAN，50 行代码玩转 GAN 模型！【附源码】https://juejin.im/post/5b5694c5e51d4534b8582b56
万字综述之生成对抗网络（GAN）https://juejin.im/entry/5c92f8f7f265da60ea145dc8
生成对抗网络原理与应用：GAN如何使生活更美好https://www.jiqizhixin.com/articles/2017-08-23-6
玻尔兹曼机、生成随机网络与自回归网络——深度学习第二十章（二）https://zhuanlan.zhihu.com/p/50745191
生成对抗网络(GAN)相比传统训练方法有什么优势?https://www.zhihu.com/question/56171002
火热的生成对抗网络(GAN),你究竟好在哪里https://bigquant.com/community/t/topic/127988
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