https://github.com/GPflow/GPflow
Revision 320eb50180e99d7d13ac2da3271c0322ea966e6d authored by Alexander G. de G. Matthews on 14 April 2016, 09:34:44 UTC, committed by Alexander G. de G. Matthews on 14 April 2016, 09:34:44 UTC
Optimizer tolerance
- HEAD
- refs/heads/0.5.0
- refs/heads/alan/hackathon_docs
- refs/heads/andrewl/fix_GPR_posterior_leading_dim
- refs/heads/avullo-willcowley/working-bee-ef1
- refs/heads/awav/check-det
- refs/heads/awav/develop-2.0/hmc-helper
- refs/heads/awav/develop-2.0/update-parameter-docstring
- refs/heads/awav/different-stuff
- refs/heads/awav/gpflow-2.0-squared_distances
- refs/heads/awav/inference
- refs/heads/awav/kernel-structure
- refs/heads/awav/likelihoods-positive-minimum
- refs/heads/awav/natural-gradients
- refs/heads/awav/release-pip-package
- refs/heads/awav/release-testing-branch
- refs/heads/awav/tensor-functor
- refs/heads/awav/tfp
- refs/heads/awav_documentation
- refs/heads/blockkernel
- refs/heads/cone
- refs/heads/deep
- refs/heads/deep_arccos_kernel
- refs/heads/develop
- refs/heads/develop-1.0
- refs/heads/eps_conditionals
- refs/heads/fast-grad
- refs/heads/felix/pathologies_experiment
- refs/heads/fergus/anisotropy
- refs/heads/fergus/het_sgpr
- refs/heads/fergus/linear
- refs/heads/fergus/linear_noise
- refs/heads/fergus/notebook
- refs/heads/fergus/random_init_lin_noise
- refs/heads/fxsm/new_svgp
- refs/heads/gh-pages
- refs/heads/gplvm
- refs/heads/gplvm-fullcov
- refs/heads/gustavocmv/heterocedastic-gaussian-likelihood
- refs/heads/gustavocmv/multiclass-likelihood-quadrature-test
- refs/heads/gustavocmv/ndiagghquadrature-property-setter
- refs/heads/gustavocmv/varying-noise-notebook-comment
- refs/heads/hugh/broadcasting_matched_multi_sample
- refs/heads/hughsalimbeni-broadcasting-conditional
- refs/heads/icouckuy-derivatives
- refs/heads/james-vincent/sgpr
- refs/heads/jax
- refs/heads/jesper/1956/stateless_random
- refs/heads/jesper/dimobjs
- refs/heads/jesper/dimobjswtf
- refs/heads/jesper/fix_gpflux
- refs/heads/jesper/for_hv
- refs/heads/jesper/jn_gps
- refs/heads/jesper/warped_halton
- refs/heads/joelb/type-hint-config
- refs/heads/john-bradshaw/binary-class-GP
- refs/heads/john-bradshaw/derivative-observations
- refs/heads/john-bradshaw/linear-features-for-kernels
- refs/heads/john-bradshaw/linear-features-for-kernels-gpflow1.0
- refs/heads/john/linear
- refs/heads/mark/jitter
- refs/heads/master
- refs/heads/master-1.0
- refs/heads/master_profile_mnist
- refs/heads/merging-masters
- refs/heads/mnist
- refs/heads/mnist_datatypes
- refs/heads/multiclass_slicing
- refs/heads/multioutput
- refs/heads/nbtest
- refs/heads/nested_models_recompilation
- refs/heads/nicolas/sinc_kernel
- refs/heads/parallel_tests
- refs/heads/profiling_mods
- refs/heads/profiling_mods_paper
- refs/heads/pypi
- refs/heads/requirements_fix
- refs/heads/revert-1511-master
- refs/heads/robustmax_epsilon_learnable
- refs/heads/sc336/mypy-sudden-failure
- refs/heads/sc336/python-3-11
- refs/heads/sc336/sphinx_version_switcher
- refs/heads/sergio_pasc/gpflow-2.0/adapt-sgpmc-and-gpmc
- refs/heads/sergio_pasc/gpflow-2.0/adapt-sgpr
- refs/heads/sergio_pasc/gpflow-2.0/move-gplvm-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-multioutput-features-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-quadrature-tests
- refs/heads/sergio_pasc/gpflow-2.0/move-tests-methods
- refs/heads/sergio_pasc/gpflow-2.0/ordinal_regression
- refs/heads/sergio_pasc/gpflow-2.0/parameter_transform
- refs/heads/sergio_pasc/gpflow-2.0/remove_training_loop
- refs/heads/spascual/add-mailmap-file
- refs/heads/st---metaautoflow
- refs/heads/st/clean_up_broadcasting_conditionals
- refs/heads/st/fix_active_dims_2
- refs/heads/st/fix_config_module_docstring
- refs/heads/st/fix_test_method_equivalence
- refs/heads/st/fix_typo
- refs/heads/st/fxsm
- refs/heads/st/fxsm_closure
- refs/heads/st/inv_probit_jitter_arg
- refs/heads/st/new_svgp
- refs/heads/st/posterior
- refs/heads/st/posterior_with_linear_operators
- refs/heads/st/quickfix/dispatch_docs
- refs/heads/st/quickfix/posterior
- refs/heads/st/quickfix_num_latent
- refs/heads/st/rename_slow_multioutput
- refs/heads/st/reorder_covariances
- refs/heads/st/rescue_754
- refs/heads/st/snowflake_kernel
- refs/heads/st/test_cleanup
- refs/heads/st/test_for_shape_check
- refs/heads/st/test_kernel
- refs/heads/st/triangular
- refs/heads/st_FITCvsVFE_2.0
- refs/heads/stef/fxsm
- refs/heads/tf2.0-compatible
- refs/heads/transform_on_sided
- refs/heads/v1.5.1-docs
- refs/heads/va/additive_models
- refs/heads/va/gpf/conditional_kernel
- refs/heads/va/gpf/seeger_lik
- refs/heads/va/h
- refs/heads/vdutor/multiple-output-gps
- refs/heads/vincent/add-shared-mixed-mok
- refs/heads/vincent/cholesky-to-kl
- refs/heads/vincent/hotfix/preslicing-lmc
- refs/heads/vincent/hotfix/save-keras-model
- refs/heads/vincent/introspect-conditional
- refs/heads/vincent/more-predict-functions
- refs/heads/vincent/nbviewer
- refs/heads/vincent/quickfix/dynamic-shapes-quadrature
- refs/heads/vincent/quickfix/typo
- refs/heads/vincent/shared-mixed-mok
- refs/heads/vincent/st/heteroscedastic
- refs/heads/vincent/st/multi-output-likelihoods
- refs/heads/vincent/update-readme
- refs/heads/whitening
- refs/tags/0.2.1
- refs/tags/0.3.1
- refs/tags/0.3.2
- refs/tags/0.3.3
- refs/tags/0.3.4
- refs/tags/0.3.5
- refs/tags/0.4.0
- refs/tags/0.5.0
- refs/tags/1.0.0
- refs/tags/1.1.0
- refs/tags/1.1.1
- refs/tags/2.0.0-rc1
- refs/tags/v1.4.1
- refs/tags/v1.5.0
- refs/tags/v1.5.1
- refs/tags/v2.0.0
- refs/tags/v2.0.1
- refs/tags/v2.0.2
- refs/tags/v2.0.3
- refs/tags/v2.0.4
- refs/tags/v2.0.5
- refs/tags/v2.1.0
- refs/tags/v2.1.1
- refs/tags/v2.1.2
- refs/tags/v2.1.3
- refs/tags/v2.1.4
- refs/tags/v2.1.5
- refs/tags/v2.2.0
- refs/tags/v2.2.1
- refs/tags/v2.3.0
- refs/tags/v2.3.1
- refs/tags/v2.4.0
- refs/tags/v2.5.0
- refs/tags/v2.5.1
- refs/tags/v2.5.2
- refs/tags/v2.6.0
- refs/tags/v2.6.1
- refs/tags/v2.6.2
- refs/tags/v2.6.3
- 320eb50180e99d7d13ac2da3271c0322ea966e6d
Raw File 
Cook and download a directory from the Software Heritage Vault
You have requested the cooking of the directory with identifier None into a standard tar.gz archive.
Are you sure you want to continue ?
Download a directory from the Software Heritage Vault
You have requested the download of the directory with identifier None as a standard tar.gz archive.
Are you sure you want to continue ?
Cook and download a revision from the Software Heritage Vault
You have requested the cooking of the history heading to revision with identifier swh:1:rev:320eb50180e99d7d13ac2da3271c0322ea966e6d into a bare git archive.
Are you sure you want to continue ?
Download a revision from the Software Heritage Vault
You have requested the download of the history heading to revision with identifier swh:1:rev:320eb50180e99d7d13ac2da3271c0322ea966e6d as a bare git archive.
Are you sure you want to continue ?
Invalid Email !
The provided email is not well-formed.
Download link has expired
The requested archive is no longer available for download from the Software Heritage Vault.
Do you want to cook it again ?
Take a new snapshot of a software origin
If the archived software origin currently browsed is not synchronized with its upstream version (for instance when new commits have been issued), you can explicitly request Software Heritage to take a new snapshot of it.
Use the form below to proceed. Once a request has been submitted and accepted, it will be processed as soon as possible. You can then check its processing state by visiting this dedicated page. Processing "take a new snapshot" request ...
Permalinks
To reference or cite the objects present in the Software Heritage archive, permalinks based on SoftWare Hash IDentifiers (SWHIDs) must be used.
Select below a type of object currently browsed in order to display its associated SWHID and permalink.
Tip revision: 320eb50180e99d7d13ac2da3271c0322ea966e6d authored by Alexander G. de G. Matthews on 14 April 2016, 09:34:44 UTC
Merge pull request #41 from GPflow/optimizer_tolerance
Merge pull request #41 from GPflow/optimizer_tolerance
Tip revision: 320eb50
RELEASE.md
# Release 0.1.2
- Included the ability to compute the full covaraince matrix at predict time. See `GPModel.predict_f`
- Included the ability to sample from the posterior function values. See `GPModel.predict_f_samples`
- Unified code in conditionals.py: see deprecations in `gp_predict`, etc.
- Added SGPR method (Sparse GP Regression)
# Release 0.1.1
- included the ability to use tensorflow's optimizers as well as the scipy ones
# Release 0.1.0
The initial release of GPflow.
The diff you're trying to view is too large. Only the first 1000 changed files have been loaded.
Computing file changes ...
