Revision d048736df973ccaf2bc8efd03f04c33893941a40 authored by st-- on 27 October 2019, 16:28:49 UTC, committed by Artem Artemev on 27 October 2019, 16:28:49 UTC
Explicitly sets the default optimization method for Scipy() to L-BFGS-B (as in gpflow1), instead of letting scipy.minimize() figure it out. This resulted in BFGS, which may be too aggressive when encountering complex optimization surfaces, so L-BFGS-B may be a more sensible default.
1 parent ca40b13
model_options.rst
========================
The six core models of GPflow
========================
.. automodule:: gpflow.models
GP Regression
-------------
.. autoclass:: gpflow.models.GPR
Sparse GP Regression
--------------------
See also the documentation of the `derivation <notebooks/SGPR_notes.html>`_.
.. autoclass:: gpflow.models.SGPR
Variational Gaussian Approximation
----------------------------------
See also the documentation of the `derivation <notebooks/VGP_notes.html>`_.
.. autoclass:: gpflow.models.VGP
Sparse Variational Gaussian Approximation
-----------------------------------------
.. autoclass:: gpflow.models.SVGP
Markov Chain Monte Carlo
------------------------
.. autoclass:: gpflow.models.GPMC
Sparse Markov Chain Monte Carlo
-------------------------------
.. autoclass:: gpflow.models.SGPMC
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