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Dingfeng Shi edited this page Dec 18, 2020
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这里记录了平时阅读论文的笔记,有时候不是完全属于论文的内容,可能有其他的拓展。
- Show And Tell模型以及一些文本的评估标准
- SCA-CNN阅读以及Tensorflow使用中碰到的一些问题
- StackGAN论文笔记
- Improved Techniques for Training GANs阅读笔记
- Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space 阅读笔记
- Generating Images with Perceptual Similarity Metrics based on Deep Networks阅读笔记
- DCGAN,将CNN应用于GAN中的成功例子
- Image to Image Translation with Conditional Adversarial Networks阅读笔记
- Real Time Single Image and Video Super Resolution Using an Efficient Sub Pixel Convolutional Neural Network阅读笔记
- 强化学习:策略梯度
- 强化学习:估值网络(Q-learning)
- 强化学习:Actor critic (A2C、A3C、Pathwise Derivative Policy Grandient)
- 强化学习:稀疏梯度的处理
- 强化学习:模仿学习(imitation learning)
- 变分贝叶斯方法
- 马尔可夫 蒙特卡洛(MCMC)与MH算法
- GAN目前常用的loss函数
- KL散度、JS散度、支撑集(support)、流形(mainfold)、测度(measure)
- 向量范数、矩阵范数
- f散度,Jensen不等式,fenchel共轭
- [转]最大熵模型
- Group Normalization
- SPECTRAL NORMALIZATION——提高多种类GAN的生成质量
- [转]CVPR 2018 Best Paper Taskonomy 作者解读
- Kubuntu 18.04 远程桌面连接XRDP的配置
- Pyside2下opencv找不到xcb库(qt.qpa.plugin:Could not load the Qt platform plugin "xcb")
- Blender或者其他非系统Python使用pip库时找不到Python.h
- SRGAN、LRGAN
- PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY , STABILITY , AND VARIATION
- pixel2pixel HD
- Combining markov random fields and convolutional neural networks for image synthesis
- High Resolution Image Inpainting using Multi Scale Neural Patch Synthesis
- GP GAN: Towards Realistic High Resolution Image Blending
- Generative Image Inpainting with Contextual Attention
- Unpaired Image to Image Translation using Cycle Consistent Adversarial Networks