Gpflow

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Breaking Changes

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Known Caveats

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Major Features and Improvements

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Bug Fixes and Other Changes

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Thanks to our Contributors

This release contains contributions from:

<INSERT>, <NAME>, <HERE>, <USING>, <GITHUB>, <HANDLE>

This patch release adds support for Tensorflow 2.16.

Bug Fixes and Other Changes

* Support and test against Tensorflow 2.16. **Note that (like tensorflow-probability) GPflow uses Keras 2. Since TF 2.16 defaults to Keras 3, `tf.keras` must now be imported from the `tf_keras` package. Alternatively, you can import `tf_keras` from the `gpflow.keras` module, which will automatically select the right source depending on which version of TF is installed.**

Thanks to our Contributors

This release contains contributions from:

uri-granta

This patch release fixes a number of identified issues.

Bug Fixes and Other Changes

* Support pickling Scipy optimizers with a non-empty compile cache
* Allow setting a prior for A in the `Linear` mean function
* Avoid rounding small values in kernel summary printout
* Test against Tensorflow 2.15

Thanks to our Contributors

This release contains contributions from:

JSchmiegel, uri-granta

This release adds caching of compiled graphs inside the Scipy optimizer, and adds support
for returning loss history. It also adds supports for Python 3.11.

Major Features and Improvements

* Support returning loss history with Scipy optimizer.
* Scipy minimize wrapper caches compiled graphs and re-uses them if called with the same arguments.
This functionality can be disabled by setting the new `compile_cache_size` argument to 0.

Bug Fixes and Other Changes

* Support and test with Python 3.11
* Test against a 'production' environment (in addition to 'min' and 'max' environments).

Thanks to our Contributors

This release contains contributions from:

khurram-ghani, jesnie, uri-granta

A small fix to ensure support for (and testing with) TensorFlow 2.12.

Bug Fixes and Other Changes

* Support and test with TensorFlow 2.12

Thanks to our Contributors

This release contains contributions from:

uri-granta

The main focus of this release is to provide users control over arguments for `tf.function`
compilation inside the Scipy minimize wrapper. It also adds support for a new categorical kernel.

Major Features and Improvements

* Added a new categorical kernel that implements categorical variables by mapping them to values in
a latent space. (2055)
* Added support for passing `tf.function` arguments for compilation in `gpflow.optimizers.Scipy`.
(2064)
* Default lower bound for parameters of scalar likelihoods can now be set via configuration.
(1985, 2066)

Bug Fixes and Other Changes

* Fixed some notebook typos and a link. (2052, 2057)
* Fixed missing docs for `SquaredExponential` and `Constant` kernels. (2056, 2063)

Thanks to our Contributors

This release contains contributions from:

sc336, partev, khurram-ghani, uri-granta, awav, jesnie