diff --git a/report_thesis/src/sections/background/ensemble_learning_models/ngboost.tex b/report_thesis/src/sections/background/ensemble_learning_models/ngboost.tex
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@@ -1,5 +1,5 @@
 \subsubsection{Natural Gradient Boosting (NGBoost)}
-\gls{ngboost} is a variant of the gradient boosting algorithm that leverages the concept of natural gradients with the goal of improving convergence speed and model performance.
+\gls{ngboost}\cite{duan_ngboost_2020} is a variant of the gradient boosting algorithm that leverages the concept of natural gradients with the goal of improving convergence speed and model performance.
 In more complex models, the parameter space can be curved and thus non-Euclidean, making the standard gradient descent less effective.
 Consequently, using the standard gradient descent can lead to slow convergence and suboptimal performance.
 In such scenarios, the application of natural gradients becomes particularly advantageous.