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__init__.py
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[SSGPLVM] migrate SSGPLVM to params branch
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2014-02-25 16:09:26 +00:00 |
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bayesian_gplvm.py
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Dont call parameters_changed ever yourself anymore and parameters are now inplace once in memory
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2014-03-04 17:32:46 +00:00 |
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bcgplvm.py
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_highest_parent_ now follows the tree, dK_dX > gradient_X, added update_grads_variational to linear, bgplvm for new framework
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2014-02-10 15:12:49 +00:00 |
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gp_classification.py
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some tifying in the models classes
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2013-12-12 14:18:18 +00:00 |
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gp_multioutput_regression.py
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some tifying in the models classes
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2013-12-12 14:18:18 +00:00 |
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gp_regression.py
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Dont call parameters_changed ever yourself anymore and parameters are now inplace once in memory
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2014-03-04 17:32:46 +00:00 |
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gplvm.py
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observable pattern through and thorugh
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2014-02-26 15:46:14 +00:00 |
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gradient_checker.py
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Fixed likelihood tests for new parameters structure
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2014-02-07 15:16:52 +00:00 |
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mrd.py
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Dont call parameters_changed ever yourself anymore and parameters are now inplace once in memory
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2014-03-04 17:32:46 +00:00 |
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sparse_gp_classification.py
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getstate > _getstate and setstate > _setstate
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2014-01-24 15:48:23 +00:00 |
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sparse_gp_multioutput_regression.py
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Fixing W_columns and num_outputs nomenclature
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2013-09-23 17:29:33 +01:00 |
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sparse_gp_regression.py
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sparse gp with uncertain inputs
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2014-03-03 15:08:54 +00:00 |
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sparse_gplvm.py
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_highest_parent_ now follows the tree, dK_dX > gradient_X, added update_grads_variational to linear, bgplvm for new framework
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2014-02-10 15:12:49 +00:00 |
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ss_gplvm.py
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switch input_sensitivity function to model
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2014-03-04 14:25:11 +00:00 |
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svigp_regression.py
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getstate > _getstate and setstate > _setstate
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2014-01-24 15:48:23 +00:00 |
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warped_gp.py
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getstate > _getstate and setstate > _setstate
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2014-01-24 15:48:23 +00:00 |
