Adding cross referencing.
========================
-The six models of GPflow
+The six core models of GPflow
========================
+The following table summarizes the six core model options in GPflow.
+
++----------------------+--------------------------+----------------------------+-----------------------------+
+| | Gaussian | Non-Gaussian (variational) | Non-Gaussian |
+| | Likelihood | | (MCMC) |
++======================+==========================+============================+=============================+
+| Full-covariance | :class:`GPflow.gpr.GPR` | :class:`GPflow.vgp.VGP` | :class:`GPflow.gpmc.GPMC` |
++----------------------+--------------------------+----------------------------+-----------------------------+
+| Sparse approximation | :class:`GPflow.sgpr.SGPR`| :class:`GPflow.svgp.SVGP` | :class:`GPflow.sgpmc.SGPMC` |
++----------------------+--------------------------+----------------------------+-----------------------------+
+
+The GPLVM, which add latent variables is also included (`notebook <notebooks/GPLVM.html>`_).
+
GP Regression
-------------
@@ -12,12 +25,16 @@ GP Regression
Sparse GP Regression
--------------------
+See also the documentation of the 'derivation <notebooks/SGPR_notes.html>'_.
+
.. automodule:: GPflow.sgpr
.. autoclass:: GPflow.sgpr.SGPR
Variational Gaussian Approximation
----------------------------------
+See also the documentation of the 'derivation <notebooks/VGP_notes.html>'_.
+
.. automodule:: GPflow.vgp
.. autoclass:: GPflow.vgp.VGP
