THeory section added to tuts

MelJan · Apr 22, 2017 · af7dd26 · af7dd26
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diff --git a/docs/tutorials/Binary_RBM_MNIST_small.rst b/docs/tutorials/Binary_RBM_MNIST_small.rst
@@ -4,9 +4,14 @@ Small centered/normal binary RBM on MNIST
 Example for training a centered and normal Binary Restricted Boltzmann machine on the MNIST handwritten digit dataset and the flipped version.
 The model is small enough to calculate the exact Log-Likelihood and annealed importance sampling and reverse annealed importance sampling are evaluated.
 
+Theory
+***********
+
 For an analysis of advantage of centering in RBMs see `How to Center Deep Boltzmann Machines. Melchior, J., Fischer, A., & Wiskott, L.. (2016). Journal of Machine Learning Research, 17(99), 1–61. <http://jmlr.org/papers/v17/14-237.html>`_
 
-If you are new on RBMs, a good theoretical introduction is given by `Course Material ICA <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following video.
+If you are new on RBMs, have a look into my `master's theses <https://www.ini.rub.de/PEOPLE/wiskott/Reprints/Melchior-2012-MasterThesis-RBMs.pdf>`_
+
+A good theoretical introduction is also given by `Course Material RBMs <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following video.
 
 .. raw:: html
 

diff --git a/docs/tutorials/ICA_natural_images.rst b/docs/tutorials/ICA_natural_images.rst
@@ -6,7 +6,26 @@ Independent Component Analysis on a natural image patches
 Example for Independent Component Analysis (`ICA <https://en.wikipedia.org/wiki/Principal_component_analysis>`_)
 on natural image patches. The independent components (columns of the ICA projection matrix) of natural image patches are edge detector filters.
 
-See  `ICA_2D_example <ICA_2D_example.html#ICA_2D_example>`__ for a theoretical introduction.
+Theory
+***********
+
+If you are new on ICA and blind source separation, a good theoretical introduction is given by `Course Material ICA <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following videos.
+
+.. raw:: html
+
+    <div style="margin-top:10px;">
+      <iframe width="560" height="315" src="http://www.youtube.com/embed/3eWuUWODE4o" frameborder="0" allowfullscreen></iframe>
+    </div>
+
+and the follow up video introduces to ICA.
+
+.. raw:: html
+
+    <div style="margin-top:10px;">
+      <iframe width="560" height="315" src="http://www.youtube.com/embed/ugiMhRbFnTo" frameborder="0" allowfullscreen></iframe>
+    </div>
+
+See also `ICA_2D_example <ICA_2D_example.html#ICA_2D_example>`__ first.
 
 Results
 ***********

diff --git a/docs/tutorials/PCA_2D_example.rst b/docs/tutorials/PCA_2D_example.rst
@@ -6,7 +6,10 @@ Principal Component Analysis 2D example.
 Example for Principal Component Analysis (`PCA <https://en.wikipedia.org/wiki/Principal_component_analysis>`_) on a linear 2D mixture.
 
 
-If you are new on PCA, a good theoretical introduction is given by `Course Material ICA <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following videos.
+Theory
+***********
+
+If you are new on PCA, a good theoretical introduction is given by `Course Material PCA <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following videos.
 
 .. raw:: html
 

diff --git a/docs/tutorials/PCA_eigenfaces.rst b/docs/tutorials/PCA_eigenfaces.rst
@@ -5,7 +5,18 @@ Eigenfaces
 
 Example for Principal Component Analysis (PCA) on face images also known as `Eigenfaces <https://en.wikipedia.org/wiki/Eigenface>`_
 
-See  `PCA_2D_example <PCA_2D_example.html#PCA_2D_example>`__ for a theoretical introduction.
+Theory
+***********
+
+If you are new on PCA, a good theoretical introduction is given by `Course Material PCA <https://www.ini.rub.de/PEOPLE/wiskott/Teaching/Material/index.html>`_ and in the following videos.
+
+.. raw:: html
+
+    <div style="margin-top:10px;">
+      <iframe width="560" height="315" src="http://www.youtube.com/embed/9H-1FH1gn6w" frameborder="0" allowfullscreen></iframe>
+    </div>
+
+See also `PCA_2D_example <PCA_2D_example.html#PCA_2D_example>`__ first.
 
 Results
 ***********