https://github.com/GPflow/GPflow
Revision 6bb7e1591d1068b2a673ee7d888562c5f2a9dac3 authored by James Hensman on 29 June 2016, 10:29:55 UTC, committed by James Hensman on 29 June 2016, 10:29:55 UTC
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Tip revision: 6bb7e1591d1068b2a673ee7d888562c5f2a9dac3 authored by James Hensman on 29 June 2016, 10:29:55 UTC
minor edits to docstrings
minor edits to docstrings
Tip revision: 6bb7e15
RELEASE.md
# Release 0.1.4
- Updated to work with tensorflow 0.9
- Added a Logistic transform to enable contraining a parameter between two bounds
- Added a Laplace distribution to use as a prior
- Added a periodic kernel
- Several improvements to the AutoFlow mechanism
- added FITC approximation (see comparison notebook)
- improved readability of code according to pep8
- significantly improved the speed of the test suite
- allowed passing of the 'tol' argument to scipy.minimize routine
- added ability to add and multiply MeanFunction objects
- Several new contributors (see README.md)
# Release 0.1.3
- Removed the need for a fork of TensorFlow. Some of our bespoke ops are replaced by equivalent versions.
# 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.
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