Tensorflow-probability

Release notes

This is the 0.24.0 release of TensorFlow Probability. It is tested and stable against TensorFlow 2.16.1 and JAX 0.4.25 .

NOTE: In TensorFlow 2.16+, `tf.keras` (and `tf.initializers`, `tf.losses`, and `tf.optimizers`) refers to Keras 3. TensorFlow Probability is not compatible with Keras 3 -- instead TFP is continuing to use Keras 2, which is now packaged as `tf-keras` and `tf-keras-nightly` and is imported as `tf_keras`. When using TensorFlow Probability with TensorFlow, you must explicitly install Keras 2 along with TensorFlow (or install `tensorflow-probability[tf]` or `tfp-nightly[tf]` to automatically install these dependencies.)


Change notes

- TensorFlow Probability now supports Python 3.12.
* But note that many parts of `tfp.layers` and `tfp.experimental.nn` will raise errors because of a TensorFlow + wrapt bug (see https://github.com/tensorflow/tensorflow/issues/60687 ), which can be worked around by setting the environment variable `WRAPT_DISABLE_EXTENSIONS=true`.

- Added an experimental implementation of Chopin, Jacob, Papaspiliopoulos, "SMC^2: an efficient algorithm for sequential analysis of state-space models", Journal of the Royal Statistical Society Series B: Statistical Methodology 75.3 (2013). See https://github.com/tensorflow/probability/blob/v0.24.0/tensorflow_probability/python/experimental/mcmc/particle_filter.py#L766 .

- Added `tfp.experimental.fastgp`, a library for approximately training and evaluating Gaussian Processes in sub-O(n^3) time.
See https://github.com/tensorflow/probability/tree/r0.24/tensorflow_probability/python/experimental/fastgp .


Huge thanks to all the contributors to this release!

- Alessandro Slamitz
- Christopher Suter
- Colin Carroll
- Emily Fertig
- Gareth Williams
- Jacob Burnim
- Jake VanderPlas
- Matthew Feickert
- Pavel Sountsov
- Richard Levasseur
- Srinivas Vasudevan
- Thomas Colthurst
- Urs Köster

Release notes

This is the 0.23.0 release of TensorFlow Probability. It is tested and stable against TensorFlow 2.15.0 and JAX 0.4.20 .


Change notes

[coming soon]

Huge thanks to all the contributors to this release!

- Christopher Suter
- Colin Carroll
- Jacob Burnim
- Juan Martinez
- Sergei Lebedev
- Sophia Gu
- Srinivas Vasudevan

Release notes

This is the 0.22.1 release of TensorFlow Probability. It is tested and stable against TensorFlow 2.14.0 and JAX 0.4.16 and 0.4.19 .


Change notes

See the release note for TFP 0.22.0 at https://github.com/tensorflow/probability/releases/tag/v0.22.0 .

Fixes some NumPy deprecation warnings by no longer casting size-1 arrays to ints.

Dependency typing_extensions is no longer pinned to <4.6.0.

Support for Python 3.8 has been removed starting with TensorFlow Probability 0.22.0.


Huge thanks to all the contributors to this release!

- Brian Patton
- Colin Carroll
- Du Phan
- Emily Fertig
- Fiona Lang
- Frederik Gossen
- Gabriel Rasskin
- Haotian Chen
- Jacob Burnim
- Jake VanderPlas
- Mark McDonald
- Oskar Fernlund
- Pavel Sountsov
- Richard Levasseur
- Salman Faroz
- Sergei Lebedev
- Srinivas Vasudevan
- Thomas Colthurst
- Urs Köster
- Yu Feng

Release notes

This is the 0.22 release of TensorFlow Probability. It is tested and stable against TensorFlow 2.14.0 and JAX 0.4.16 .


Change notes

Support for Python 3.8 has been removed starting with TensorFlow Probability 0.22.0.

[Coming soon.]


Huge thanks to all the contributors to this release!

- Brian Patton
- Colin Carroll
- Du Phan
- Emily Fertig
- Fiona Lang
- Frederik Gossen
- Gabriel Rasskin
- Haotian Chen
- Jacob Burnim
- Jake VanderPlas
- Mark McDonald
- Oskar Fernlund
- Pavel Sountsov
- Richard Levasseur
- Salman Faroz
- Srinivas Vasudevan
- Thomas Colthurst
- Urs Köster
- Yu Feng

Release notes

This is the 0.21.0 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.13 and JAX 0.4.14 .

Change notes
[no major changes]


Huge thanks to all the contributors to this release!

- bjp
- chansoo
- colcarroll
- emilyaf
- feyu
- flang
- Jacob Burnim
- jburnim
- jcater
- juanantoniomc
- Matthew Feickert
- oskarfernlund
- phawkins
- schwartzedward
- siege
- Srinivas Vasudevan
- ursk

Release notes

This is the 0.20 release of TensorFlow Probability. It is
tested and stable against TensorFlow version 2.12 and JAX 0.4.8 .

Change notes

- Add `LinearOperatorBasis` and `LinearOperatorRowBlock`.
- Ensure `Dirichlet` and `RelaxedOneHotCategorical` transform correctly under bijectors.
- Add `SphericalSpace` and use in all Spherical Distributions
- Add `GeneralSpace.transform_general`
- Fix guitar numpy rewrite_equivalence_test.
- BREAKING CHANGE: Ignore deprecated `always_yield_multivariante_normal` arg to `tfd.GaussianProcess` and `tfd.GaussianProcessRegressionModel` so that event shape is always [1] for a single index point.
- Create a `bayesopt` submodule of TFP experimental and add acquisition functions.
- Add the `FeatureScaledWithCategorical` kernel, a PSD kernel over structures of continuous and categorical data, to TFP experimental.
- [BREAKING] Remove deprecated arg BDF.use_pfor_to_compute_jacobian.

Huge thanks to all the contributors to this release!

- ashishenoy
- atondwal
- bjp
- Christopher Suter
- colcarroll
- Colin Carroll
- emilyaf
- fdtomasi
- flang
- Jacob Burnim
- jburnim
- jcater
- juanantoniomc
- langmore
- Leandro Campos
- leben
- Matthew Feickert
- mmladenov
- nkovela
- Pavel Sountsov
- phandu
- phawkins
- power
- S. Amin
- siege
- Srinivas Vasudevan
- synandi
- thomaswc
- Tirumalesh
- ujaved
- ursk