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dingfengshi / DeepLeraningNotes Public

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强化学习：Actor critic (A2C、A3C、Pathwise Derivative Policy Grandient)

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DingfengShi edited this page Jun 23, 2018 · 1 revision

Toggle table of contents Pages 46

Home
3D CV基础（一）
3D CV基础（五）参数评估
3D CV基础（六）常用的图像处理
3D CV基础（四）对极几何
3D CV（三）投影变换
3D CV（二）相机模型
Blender或者其他非系统Python使用pip库时找不到Python.h
Combining markov random ﬁelds and convolutional neural networks for image synthesis
DCGAN，将CNN应用于GAN中的成功例子
Estimator的一些细节
f散度，Jensen不等式，fenchel共轭
GAN目前常用的loss函数
Generating Images with Perceptual Similarity Metrics based on Deep Networks阅读笔记
Generative Image Inpainting with Contextual Attention
GP GAN: Towards Realistic High Resolution Image Blending
Group Normalization
High Resolution Image Inpainting using Multi Scale Neural Patch Synthesis
Image to Image Translation with Conditional Adversarial Networks阅读笔记
Improved Techniques for Training GANs阅读笔记
KL散度、JS散度、支撑集（support)、流形(mainfold)、测度（measure）
Kubuntu 18.04 远程桌面连接XRDP的配置
pixel2pixel HD
Plug & Play Generative Networks: Conditional Iterative Generation of Images in Latent Space 阅读笔记
PROGRESSIVE GROWING OF GANS FOR IMPROVED QUALITY , STABILITY , AND VARIATION
Pyside2下opencv找不到xcb库（qt.qpa.plugin:Could not load the Qt platform plugin "xcb"）
PyTorch文档阅读笔记
Real Time Single Image and Video Super Resolution Using an Efﬁcient Sub Pixel Convolutional Neural Network
SCA CNN阅读以及Tensorflow使用中碰到的一些问题
Show And Tell模型以及一些文本的评估标准
SPECTRAL NORMALIZATION——提高多种类GAN的生成质量
SRGAN、LRGAN
StackGAN复现中的一些细节
StackGAN论文笔记
TfRecord的一些坑
Unpaired Image to Image Translation using Cycle Consistent Adversarial Networks
从TFGAN的LOSS引申开来，阅读源码后的一些理解
凸函数基础
变分贝叶斯方法
向量范数、矩阵范数
强化学习：Actor critic (A2C、A3C、Pathwise Derivative Policy Grandient)
强化学习：估值网络（Q learning）
强化学习：模仿学习(imitation learning)
强化学习：稀疏梯度的处理
强化学习：策略梯度
马尔可夫蒙特卡洛（MCMC）与MH算法

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