Nomenclature. Because people gets confused with weird symbols

Chapter1/chapter1.tex

@@ -66,4 +66,25 @@ \section{Our Contribution}
 This work builds on the foundations laid out by Blundell et al. \cite{blundell2015weight}, who introduced \textit{Bayes by Backprop} for feedforward neural networks. Together with the extension to recurrent neural networks, introduced by Fortunato et al. \cite{fortunato2017bayesian}, \textit{Bayes by Backprop} is now applicable on the three most frequently used types of neural networks, i.e., feedforward, recurrent, and convolutional neural networks.
 
 
-%\nomenclature[z-cif]{$CIF$}{Cauchy's Integral Formula} % first letter Z is for Acronyms 
+\nomenclature[z-cnn]{$CNN$}{Convolution Neural Networks} 
+\nomenclature[z-mnist]{$MNIST$}{Modified National Institute of Standards and Technology} 
+\nomenclature[z-cifar]{$CIFAR$}{Canadian Institute for Advanced Research} 
+\nomenclature[z-dnn]{$DNN$}{Deep Neural Networks} 
+\nomenclature[z-ann]{$ANN$}{Artificial Neural Networks} 
+\nomenclature[z-lgb]{$LGB$}{Lateral Geniculate Body} 
+\nomenclature[z-kl]{$KL$}{Kullback–Leibler} 
+\nomenclature[z-cov]{$Cov$}{Covariance} 
+\nomenclature[z-sgvb]{$SGVB$}{Stochastic Gradient Variational Bayes} 
+\nomenclature[z-rnn]{$RNN$}{Recurrent Neural Networks} 
+\nomenclature[z-gru]{$GRU$}{Gated Recurrent Units} 
+\nomenclature[z-vi]{$VI$}{Variational Inference} 
+\nomenclature[z-mean]{$\mu_{ijhw}$}{Mean} 
+\nomenclature[z-variance]{$\alpha_{ijhw}\mu^2_{ijhw}$}{Variance} \nomenclature[z-kl]{$q_{\theta}(w|\mathcal{D})$}{Variational Posterior Probability Distribution} 
+\nomenclature[z-relu]{$ReLU,$}{Rectified Linear Unit} 
+\nomenclature[z-mle]{$MLE$}{Maximum Likelihood Estimation}
+\nomenclature[z-map]{$MAP$}{maximum a posteriori} 
+\nomenclature[z-sr]{$SR$}{Super Resolution} 
+\nomenclature[z-lr]{$LR$}{Low Resolution} 
+\nomenclature[z-hr]{$HR$}{High Resolution} 
+\nomenclature[z-gan]{$GAN$}{Generative Adversarial Networks}
+\nomenclature[z-dcgan]{$DCGAN$}{Deep Convolutional Generative Adversarial Networks}