Update documentation and add some references on the computation of co…

…unterfactual explanations

docs/faq.rst

@@ -46,6 +46,9 @@ Can you implement a particular method/algorithm?
 
     Go to Github_ and create a new issue. I will take a look at it and let you know whether/when I will/can implement this.
 
+Where can I learn more about the computation of counterfactual explanations?
+    Please take a look at the section :ref:`theory_background`.
+
 
 .. _License: https://github.com/andreArtelt/ceml/LICENSE
 .. _Github: https://github.com/andreArtelt/ceml/

docs/index.rst

@@ -8,9 +8,9 @@ CEML is a Python toolbox for computing counterfactuals. Counterfactuals can be u
 
 It supports many common machine learning frameworks:
 
-    - scikit-learn (0.23.1)
-    - PyTorch (1.5.0)
-    - Keras & Tensorflow (2.2.0)
+    - scikit-learn (0.23.2)
+    - PyTorch (1.6.0)
+    - Keras & Tensorflow (2.2.1)
 
 Furthermore, CEML is easy to use and can be extended very easily. See the following user guide for more information on how to use and extend ceml.
 
@@ -22,6 +22,7 @@ Furthermore, CEML is easy to use and can be extended very easily. See the follow
     installation
     tutorial
     advanced
+    theory_background
     faq
 
 

docs/theory_background.rst

@@ -0,0 +1,13 @@
+.. _theory_background:
+
+************************************************************************
+Theoretical background on the computation of counterfactual explanations
+************************************************************************
+
+References
+==========
+Details on the computation of counterfactual explanations can be found in the following papers:
+
+    - `On the computation of counterfactual explanations -- A survey <https://arxiv.org/abs/1911.07749>`_
+    - `Efficient computation of counterfactual explanations of LVQ models <https://arxiv.org/abs/1908.00735>`_
+    - `Convex Density Constraints for Computing Plausible Counterfactual Explanations <https://arxiv.org/abs/2002.04862>`_