diff --git a/Chapter16/structured_probabilistic_modelling.tex b/Chapter16/structured_probabilistic_modelling.tex
index de856d9..cc92293 100644
--- a/Chapter16/structured_probabilistic_modelling.tex
+++ b/Chapter16/structured_probabilistic_modelling.tex
@@ -86,7 +86,7 @@ \section{非结构化建模的挑战}
 	即使样本只有一个从错误分布中产生的元素，那么采样的过程肯定是错误的。 
 \end{itemize}
 
-图\ref{fig:chap16_polar}中描述了一个使用较小的自然图片的采样任务。
+图\ref{fig:chap16_fig-ssrbm}中描述了一个使用较小的自然图片的采样任务。
 % 551 ok 
 
 \begin{figure}[!htb]
@@ -101,7 +101,7 @@ \section{非结构化建模的挑战}
 	\centerline{\includegraphics{Chapter16/figures/fig-ssrbm_samples}}	
 \fi
 	\caption{TODO}
-	\label{fig:chap16_polar}
+	\label{fig:chap16_fig-ssrbm}
 \end{figure}
 
 对上千甚至是上百万的随机变量的分布建模，无论从计算上还是从统计意义上说，都是一个具有挑战性的任务。
diff --git a/Chapter19/approximate_inference.tex b/Chapter19/approximate_inference.tex
index a6616a0..cbb8be9 100644
--- a/Chapter19/approximate_inference.tex
+++ b/Chapter19/approximate_inference.tex
@@ -278,7 +278,7 @@ \section{\glsentrytext{MAP}推断和\glsentrytext{sparse_coding}}
 
 
 \section{变分推断和学习}
-\label{variational_inference_and_learning}
+\label{sec:variational_inference_and_learning}
 % 629
 
 
diff --git a/deep_learning_research.tex b/deep_learning_research.tex
index 87d33a3..d15ef2b 100644
--- a/deep_learning_research.tex
+++ b/deep_learning_research.tex
@@ -3,12 +3,11 @@ \part{深度学习研究}
 \label{part:deep_learning_research}
 
 
-\input{Chapter13/linear_factor_models.tex}
-\input{Chapter14/autoencoders.tex}
-\input{Chapter15/representation_learning.tex}
-\input{Chapter16/structured_probabilistic_modelling.tex}
-\input{Chapter17/monte_carlo_methods.tex}
-\input{Chapter18/confronting_the_partition_function.tex}
-\input{Chapter19/approximate_inference.tex}
-%\input{Chapter20/deep_generative_models.tex}
-
+%\input{Chapter13/linear_factor_models.tex}
+%\input{Chapter14/autoencoders.tex}
+%\input{Chapter15/representation_learning.tex}
+%\input{Chapter16/structured_probabilistic_modelling.tex}
+%\input{Chapter17/monte_carlo_methods.tex}
+%\input{Chapter18/confronting_the_partition_function.tex}
+%\input{Chapter19/approximate_inference.tex}
+\input{Chapter20/deep_generative_models.tex}
diff --git a/dlbook_cn.tex b/dlbook_cn.tex
index d2c7055..33cbc7a 100644
--- a/dlbook_cn.tex
+++ b/dlbook_cn.tex
@@ -70,6 +70,11 @@
 \newcommand{\firstall}[1]{\textbf{\gls{#1}}~(\glsdesc{#1}, \glssymbol{#1})}
 \newcommand{\ENNAME}[1]{\text{#1}}
 \newcommand{\NUMTEXT}[1]{\text{#1}}
+\newcommand{\figref}[1]{图\ref{#1}}
+\newcommand{\chapref}[1]{第\ref{#1}章}
+\newcommand{\secref}[1]{第\ref{#1}节}
+\newcommand{\eqnref}[1]{式\eqref{#1}}
+
 
 % Draft
 \usepackage{draftwatermark}
diff --git a/math_symbol.tex b/math_symbol.tex
index ed74f1e..45ae083 100644
--- a/math_symbol.tex
+++ b/math_symbol.tex
@@ -1,6 +1,6 @@
 % !Mode:: "TeX:UTF-8"
-\newcommand{\argmax}{\arg\max}
-\newcommand{\argmin}{\arg\min}
+\newcommand{\argmax}{\arg\,\max}
+\newcommand{\argmin}{\arg\,\min}
 \newcommand{\norm}[1]{\left\lVert#1\right\rVert}
 \newcommand{\Tr}{\text{Tr}}
 
diff --git a/terminology.tex b/terminology.tex
index 9d3b67a..62e4ca9 100644
--- a/terminology.tex
+++ b/terminology.tex
@@ -108,16 +108,16 @@
 \newglossaryentry{ANN}
 {
   name=人工神经网络,
-  description={artificial neural networks},
-  sort={artificial neural networks},
+  description={artificial neural network},
+  sort={artificial neural network},
   symbol={ANN}
 }
 
 \newglossaryentry{NN}
 {
   name=神经网络,
-  description={neural networks},
-  sort={neural networks},
+  description={neural network},
+  sort={neural network},
 }
 
 \newglossaryentry{SGD}
@@ -303,8 +303,8 @@
 \newglossaryentry{critical_points}
 {
   name=临界点,
-  description={critical points},
-  sort={critical points},
+  description={critical point},
+  sort={critical point},
 }
 
 \newglossaryentry{stationary_point}
@@ -337,8 +337,8 @@
 \newglossaryentry{saddle_points}
 {
   name=鞍点,
-  description={saddle points},
-  sort={saddle points},
+  description={saddle point},
+  sort={saddle point},
 }
 
 \newglossaryentry{global_minimum}
@@ -351,8 +351,8 @@
 \newglossaryentry{partial_derivatives}
 {
   name=偏导数,
-  description={partial derivatives},
-  sort={partial derivatives},
+  description={partial derivative},
+  sort={partial derivative},
 }
 
 \newglossaryentry{gradient}
@@ -506,15 +506,15 @@
 \newglossaryentry{equality_constraints}
 {
   name=等式约束,
-  description={equality constraints},
-  sort={equality constraints},
+  description={equality constraint},
+  sort={equality constraint},
 }
 
 \newglossaryentry{inequality_constraints}
 {
   name=不等式约束,
-  description={inequality constraints},
-  sort={inequality constraints},
+  description={inequality constraint},
+  sort={inequality constraint},
 }
 
 \newglossaryentry{regularization}
@@ -672,7 +672,6 @@
   symbol={CNN}
 }
 
-
 \newglossaryentry{mcmc}
 {
   name=马尔可夫链蒙特卡罗,
@@ -718,7 +717,7 @@
 
 \newglossaryentry{partition_function}
 {
-  name=分割函数,
+  name=配分函数,
   description={Partition Function},
   sort={Partition Function},
 }
@@ -760,9 +759,10 @@
 
 \newglossaryentry{VAE}
 {
-  name=变分自编码,
+  name=变分自动编码器,
   description={variational auto-encoder},
   sort={variational auto-encoder},
+  symbol={VAE},
 }
 
 \newglossaryentry{CV}
@@ -789,7 +789,7 @@
 
 \newglossaryentry{RBM}
 {
-  name=受限玻耳兹曼机,
+  name=受限玻尔兹曼机,
   description={Restricted Boltzmann Machine},
   sort={Restricted Boltzmann Machine},
   symbol={RBM}
@@ -804,21 +804,21 @@
 
 \newglossaryentry{Boltzmann}
 {
-  name=玻耳兹曼,
+  name=玻尔兹曼,
   description={Boltzmann},
   sort={Boltzmann},
 }
 
 \newglossaryentry{BM}
 {
-  name=玻耳兹曼机,
+  name=玻尔兹曼机,
   description={Boltzmann Machine},
   sort={Boltzmann Machine},
 }
 
 \newglossaryentry{DBM}
 {
-  name=深度玻耳兹曼机,
+  name=深度玻尔兹曼机,
   description={Deep Boltzmann Machine},
   sort={Deep Boltzmann Machine},
   symbol={DBM}
@@ -826,7 +826,7 @@
 
 \newglossaryentry{CBM}
 {
-  name=卷积玻耳兹曼机,
+  name=卷积玻尔兹曼机,
   description={Convolutional Boltzmann Machine},
   sort={Convolutional Boltzmann Machine},
   symbol={CBM}
@@ -1075,17 +1075,17 @@
 \newglossaryentry{HMM}
 {
   name=隐马尔可夫模型,
-  description={Hidden Markov Models},
-  sort={Hidden Markov Models},
-  symbol={HMMs}
+  description={Hidden Markov Model},
+  sort={Hidden Markov Model},
+  symbol={HMM}
 }
 
 \newglossaryentry{GMM}
 {
   name=高斯混合模型,
-  description={Gaussian Mixture Models},
-  sort={Gaussian Mixture Models},
-  symbol={GMMs}
+  description={Gaussian Mixture Model},
+  sort={Gaussian Mixture Model},
+  symbol={GMM}
 }
 
 \newglossaryentry{transcribe}
@@ -1142,8 +1142,8 @@
 \newglossaryentry{GPU}
 {
   name=图形处理器,
-  description={Graphics Processing Units},
-  sort={Graphics Processing Units},
+  description={Graphics Processing Unit},
+  sort={Graphics Processing Unit},
   symbol={GPU}
 }
 
@@ -1185,15 +1185,15 @@
 \newglossaryentry{structured_probabilistic_models}
 {
   name=结构化概率模型,
-  description={structured probabilistic models},
-  sort={structured probabilistic models},
+  description={structured probabilistic model},
+  sort={structured probabilistic model},
 }
 
 \newglossaryentry{graphical_models}
 {
   name=图模型,
-  description={graphical models},
-  sort={graphical models},
+  description={graphical model},
+  sort={graphical model},
 }
 
 \newglossaryentry{directed_graphical_model}
@@ -1523,8 +1523,8 @@
 \newglossaryentry{data_points}
 {
    name=数据点,
-   description={data points},
-   sort={data points},
+   description={data point},
+   sort={data point},
 }
 
 \newglossaryentry{label}
@@ -1558,15 +1558,15 @@
 \newglossaryentry{parameters}
 {
   name=参数,
-  description={parameters},
-  sort={parameters},
+  description={parameter},
+  sort={parameter},
 }
 
 \newglossaryentry{weights}
 {
   name=权重,
-  description={weights},
-  sort={weights},
+  description={weight},
+  sort={weight},
 }
 
 \newglossaryentry{mean_squared_error}
@@ -1580,8 +1580,8 @@
 \newglossaryentry{normal_equations}
 {
   name=标准方程,
-  description={normal equations},
-  sort={normal equations},
+  description={normal equation},
+  sort={normal equation},
 }
 
 \newglossaryentry{training_error}
@@ -1678,8 +1678,8 @@
 \newglossaryentry{benchmarks}
 {
   name=基准,
-  description={bechmarks},
-  sort={bechmarks},
+  description={bechmark},
+  sort={bechmark},
 }
 
 \newglossaryentry{point_estimator}
@@ -1840,21 +1840,21 @@
 \newglossaryentry{kernel_machines}
 {
   name=核机器,
-  description={kernel machines},
-  sort={kernel machines},
+  description={kernel machine},
+  sort={kernel machine},
 }
 \newglossaryentry{kernel_methods}
 {
   name=核方法,
-  description={kernel methods},
-  sort={kernel methods},
+  description={kernel method},
+  sort={kernel method},
 }
 
 \newglossaryentry{support_vectors}
 {
   name=支持向量,
-  description={support vectors},
-  sort={support vectors},
+  description={support vector},
+  sort={support vector},
 }
 
 \newglossaryentry{SVM}
@@ -2036,8 +2036,8 @@
 \newglossaryentry{feedforward_network}
 {
   name=前馈网络,
-  description={feedforward networks},
-  sort={feedforward networks},
+  description={feedforward network},
+  sort={feedforward network},
 }
 
 \newglossaryentry{transition}
@@ -2057,8 +2057,8 @@
 \newglossaryentry{GSN}
 {
   name=生成随机网络,
-  description={generative stochastic networks},
-  sort={generative stochastic networks},
+  description={generative stochastic network},
+  sort={generative stochastic network},
   symbol={GSN}
 }
 
@@ -2121,7 +2121,7 @@
 
 \newglossaryentry{fixed_point_equation}
 {
-  name=固定点方程,
+  name=不动点方程,
   description={fixed point equation},
   sort={fixed point equation},
 }
@@ -2150,8 +2150,8 @@
 \newglossaryentry{MRF}
 {
   name=马尔可夫随机场,
-  description={Markov random fields},
-  sort={Markov random fields},
+  description={Markov random field},
+  sort={Markov random field},
   symbol={MRF}
 }
 
@@ -2165,8 +2165,8 @@
 \newglossaryentry{log_linear_model}
 {
   name=对数线性模型,
-  description={log-linear models},
-  sort={log-linear models},
+  description={log-linear model},
+  sort={log-linear model},
 }
 
 \newglossaryentry{product_of_expert}
@@ -2212,7 +2212,7 @@
 
 \newglossaryentry{boltzmann_distribution}
 {
-  name=玻耳兹曼分布,
+  name=玻尔兹曼分布,
   description={Boltzmann distribution},
   sort={Boltzmann distribution},
 }
@@ -2522,8 +2522,8 @@
 \newglossaryentry{bits}
 {
   name=比特,
-  description={bits},
-  sort={bits},
+  description={bit},
+  sort={bit},
 }
 
 \newglossaryentry{shannons}
@@ -2639,7 +2639,7 @@
 
 \newglossaryentry{harmonium}
 {
-  name=harmonium,
+  name=簧风琴,
   description={harmonium},
   sort={harmonium},
 }
@@ -3131,8 +3131,8 @@
 \newglossaryentry{clip_gradients}
 {
   name=梯度截断,
-  description={clip gradients},
-  sort={clip gradients},
+  description={clip gradient},
+  sort={clip gradient},
 }
 
 \newglossaryentry{absolute_value_rectification}
@@ -3266,8 +3266,8 @@
 \newglossaryentry{Krylov_methods}
 {
   name=Krylov方法,
-  description={Krylov methods},
-  sort={Krylov methods},
+  description={Krylov method},
+  sort={Krylov method},
 }
 
 \newglossaryentry{parallel_distributed_processing}
@@ -3585,16 +3585,16 @@
 \newglossaryentry{ESN}
 {
   name=回声状态网络,
-  description={echo state networks},
-  sort={echo state networks},
+  description={echo state network},
+  sort={echo state network},
   symbol={ESN}
 }
 
 \newglossaryentry{liquid_state_machines}
 {
   name=流体状态机,
-  description={liquid state machines},
-  sort={liquid state machines},
+  description={liquid state machine},
+  sort={liquid state machine},
 }
 
 \newglossaryentry{reservoir_computing}
@@ -3845,15 +3845,15 @@
 \newglossaryentry{simple_cells}
 {
   name=简单细胞,
-  description={simple cells},
-  sort={simple cells},
+  description={simple cell},
+  sort={simple cell},
 }
 
 \newglossaryentry{complex_cells}
 {
   name=复杂细胞,
-  description={complex cells},
-  sort={complex cells},
+  description={complex cell},
+  sort={complex cell},
 }
 
 \newglossaryentry{fovea}
@@ -3873,9 +3873,9 @@
 \newglossaryentry{TDNNs}
 {
   name=时延神经网络,
-  description={time delay neural networks},
-  sort={time delay neural networks},
-  symbol={TDNNs}
+  description={time delay neural network},
+  sort={time delay neural network},
+  symbol={TDNN}
 }
 
 \newglossaryentry{reverse_correlation}
@@ -4210,8 +4210,8 @@
 \newglossaryentry{word_embeddings}
 {
   name=词嵌入,
-  description={word embeddings},
-  sort={word embeddings},
+  description={word embedding},
+  sort={word embedding},
 }
 
 \newglossaryentry{one_hot}
@@ -4294,8 +4294,17 @@
 \newglossaryentry{generative_adversarial_networks}
 {
   name=生成式对抗网络,
-  description={generative adversarial networks},
-  sort={generative adversarial networks},
+  description={generative adversarial network},
+  sort={generative adversarial network},
+  symbol={GAN}
+}
+
+\newglossaryentry{GAN}
+{
+  name=生成式对抗网络,
+  description={generative adversarial network},
+  sort={generative adversarial network},
+  symbol={GAN}
 }
 
 \newglossaryentry{feedforward_classifier}
@@ -4514,8 +4523,8 @@
 \newglossaryentry{matrix}
 {
   name=矩阵,
-  description={matrices},
-  sort={matrices},
+  description={matrix},
+  sort={matrix},
 }
 
 \newglossaryentry{tensor}
@@ -4859,15 +4868,15 @@
 \newglossaryentry{unsuper_learn_algo}
 {
   name=无监督学习算法,
-  description={unsupervised learning algorithms},
-  sort={unsupervised learning algorithms},
+  description={unsupervised learning algorithm},
+  sort={unsupervised learning algorithm},
 }
 
 \newglossaryentry{super_learn_algo}
 {
   name=有监督学习算法,
-  description={supervised learning algorithms},
-  sort={supervised learning algorithms},
+  description={supervised learning algorithm},
+  sort={supervised learning algorithm},
 }
 
 \newglossaryentry{word_embedding}