TensorFlow的概率方法
TensorFlow的概率方法Release notes
This is the 0.6 release of TensorFlow Probability. It is
tested and stable against TensorFlow version 1.13.1.
Change notes
- Adds tfp.positive_semidefinite_kernels.RationalQuadratic
- Support float64 in tfpl.MultivariateNormalTriL.
- Add IndependentLogistic and IndependentPoisson distribution layers.
- Add
make_value_setter
interceptor to set values of Edward2 random variables. - Implementation of Kalman Smoother, as a member function of LinearGaussianStateSpaceModel.
- Bijector caching is enabled only in one direction when executing in eager mode. May cause some performance regression in eager mode if repeatedly computing
forward(x)
orinverse(y)
with the samex
ory
value. - Handle rank-0/empty event_shape in tfpl.Independent{Bernoulli,Normal}.
- Run additional tests in eager mode.
- quantiles(x, n, ...) added to tfp.stats.
- Makes tensorflow_probability compatible with Tensorflow 2.0 TensorShape indexing.
- Use scipy.special functions when testing KL divergence for Chi, Chi2.
- Add methods to create forecasts from STS models.
- Add a MixtureSameFamily distribution layer.
- Add Chi distribution.
- Fix doc typo
tfp.Distribution
->tfd.Distribution
. - Add Gumbel-Gumbel KL divergence.
- Add HalfNormal-HalfNormal KL divergence.
- Add Chi2-Chi2 KL divergence unit tests.
- Add Exponential-Exponential KL divergence unit tests.
- Add sampling test for Normal-Normal KL divergence.
- Add an IndependentNormal distribution layer.
- Added
posterior_marginals
toHiddenMarkovModel
- Add Pareto-Pareto KL divergence.
- Add LinearRegression component for structural time series models.
- Add dataset ops to the graph (or create kernels in Eager execution) during the python Dataset object creation instead doing it during Iterator creation time.
- Text messages HMC benchmark.
- Add example notebook encoding a switching Poisson process as an HMM for multiple changepoint detection.
- Require
num_adaptation_steps
argument tomake_simple_step_size_update_policy
. - s/eight_hmc_schools/eight_schools_hmc/ in printed benchmark string.
- Add
tfp.layers.DistributionLambda
to enable plumbingtfd.Distribution
instances through Keras models. - Adding tfp.math.batch_interp_regular_1d_grid.
- Update description of fill_triangular to include an in-depth example.
- Enable bijector/distribution composition, eg,
tfb.Exp(tfd.Normal(0,1))
. - linear and midpoint interpolation added to tfp.stats.percentile.
- Make distributions include only the bijectors they use.
- tfp.math.interp_regular_1d_grid added
- tfp.stats.correlation added (Pearson correlation).
- Update list of edward2 RVs to include recently added Distributions.
- Density of continuous Uniform distribution includes the upper endpoint.
- Add support for batched inputs in tfp.glm.fit_sparse.
- interp_regular_1d_grid added to tfp.math.
- Added HiddenMarkovModel distribution.
- Add Student's T Process.
- Optimize LinearGaussianStateSpaceModel by avoiding matrix ops when the observations are statically known to be scalar.
- stddev, cholesky added to tfp.stats.
- Add methods to fit structual time series models to data with variational inference and HMC.
- Add Expm1 bijector (Y = Exp(X) - 1).
- New stats namespace. covariance and variance added to tfp.stats
- Make all available MCMC kernels compatible with TransformedTransitionKernel.
Huge thanks to all the contributors to this release!
- Adam Wood
- Alexey Radul
- Anudhyan Boral
- Ashish Saxena
- Billy Lamberta
- Brian Patton
- Christopher Suter
- Cyril Chimisov
- Dave Moore
- Eugene Zhulenev
- Griffin Tabor
- Ian Langmore
- Jacob Burnim
- Jakub Arnold
- Jiahao Yao
- Jihun
- Jiming Ye
- Joshua V. Dillon
- Juan A. Navarro Pérez
- Julius Kunze
- Julius Plenz
- Kristian Hartikainen
- Kyle Beauchamp
- Matej Rizman
- Pavel Sountsov
- Peter Roelants
- Rif A. Saurous
- Rohan Jain
- Roman Ring
- Rui Zhao
- Sergio Guadarrama
- Shuhei Iitsuka
- Shuming Hu
- Srinivas Vasudevan
- Tabor473
- ValentinMouret
- Youngwook Kim
- Yuki Nagae
Assets
2
This is the 0.6.0-rc1 release candidate of TensorFlow Probability. It is tested against TensorFlow 1.13.0-rc2.
Assets
2
Assets
2
This is the RC0 release candidate of the TensorFlow Probability 0.6 release.
It is tested against TensorFlow 1.13.0-rc0
Assets
2
Release Notes
This is the 0.5.0 release of TensorFlow Probability. It's tested and stable against TensorFlow 1.12.
Packaging Change
As of this release, we no longer package a separate GPU-specific build. Users can select the version of TensorFlow they wish to use (CPU or GPU), and TensorFlow Probability will work with both.
As a result, we no longer explicitly list a TensorFlow dependency in our package requirements (since we can't know which version the user will want). If TFP is installed with no TensorFlow package present, or with an unsupported TensorFlow version, we will issue an ImportError
at time of import.
Distributions & Bijectors
- All
Distribution
s have been relocated fromtf.distributions
totfp.distributions
(the ones in TF are deprecated and will be deleted in TF 2.0). - Add Triangular distribution.
- Add Zipf distribution.
- Add NormalCDF Bijector.
- Add Multivariate Student's t-distribution.
- Add RationalQuadratic kernel.
Documentation & Examples
- Add example showing how to fit GLMM using Variational Inference.
- Introduce Gaussian process latent variable model colab.
- Introduce Gaussian process regression example colab
- Add notebook showcasing GLM algorithms and deriving some results about GLMs that those algorithms leverage.
Huge thanks to all the contributors to this release!
- Akshay Modi
- Alexey Radul
- Anudhyan Boral
- Ashish Saxena
- Ben Zinberg
- Billy Lamberta
- Brian Patton
- Christopher Suter
- Dave Moore
- Ian Langmore
- Joshua V. Dillon
- Kristian Hartikainen
- Malcolm Reynolds
- Pavel Sountsov
- Srinivas Vasudevan
- Xiaojing Wang
- Yifei Feng
Assets
2
This is the RC1 release candidate of the TensorFlow Probability 0.5 release.
It is tested against TensorFlow 1.12.0-rc2
Assets
2
This is the RC0 release candidate of the TensorFlow Probability 0.5 release.
It is tested against TensorFlow 1.12.0-rc2
TensorFlow Probability 0.3.0-rc2
csuter released this
This is the rc1 release. We never actually built rc1, since we needed to cherrypick a few more things.
This release is tested against TensorFlow v1.10.0
TensorFlow Probability 0.2.0
csuter released this
This is the 0.2 release of TensorFlow Probability, our first versioned release.
It is tested against TensorFlow 1.9.0.
TensorFlow Probability 0.2.0-rc0
csuter released this
This is release candidate rc0, of our 0.2 release of TensorFlow Probability.
It is tested against TensorFlow 1.9.0.
TensorFlow Probability 0.1.0-rc1
csuter released this
Release 0.1.0-rc1
This is release candidate rc1, of our first versioned release of TensorFlow Probability.
It is tested against TensorFlow 1.9.0-rc1.
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创建时间： 2017-10-24 07:50:54 |
最后Commits： 昨天 |
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csuter released this
May 30, 2019
This is the 0.7.0-rc0 release of TensorFlow Probability. It is
tested and stable against TensorFlow version 1.14-rc0 and 2.0.0-alpha