TensorFlow Probability 0.5.0-rc0

This is the RC0 release candidate of the TensorFlow Probability 0.5 release.

It is tested against TensorFlow 1.12.0-rc2

TensorFlow Probability 0.4.0

Release Notes

This is the 0.4.0 release of TensorFlow Probability. It's tested and stable against TensorFlow 1.11.

Distributions & Bijectors

• All TF core Distributions now live in TFP (old ones are deprecated but still there)
• All TF core Bijectors now live in TFP (old ones are deprecated but still there)
• CDF support for Independent
• Seasonal effects and Sum components for Structural Time Series
• Add Half-Cauchy Distribution
• DCT (discrete cosine transform) Bijector
• Support dynamic shapes in BatchNormalization Bijector
• Add InverseGaussian Distribution
• Scaffolding for Bayesian Structural Time Series models
• Add VonMises Distribution
• Add Pareto distrubiton
• Implicit reparameterization for TruncatedNormal

Sampling & Inference

• Various improvements to BFGS and line search methods
• Add tape interceptor in Edward2
• GLM fitting with proximal gradient and L1/L2-regularization
• Support nested interceptors in Edward2

Documentation & Examples

• Update docs to point to tfp instead of tf/tf.contrib
• Credit card interest notebook
• Bayesian Neural Net (VGG, ResNet18) examples on CIFAR-10 data
• Disentangled Sequential Autoencoder example
• Eager-mode, single-chain No-U-Turn Sampler
• Grammar VAE example using Edward2
• Deep exponential family example using Edward2
• Latent Dirichlet Allocation example using Edward2
• Factorial Mixtures notebook

Huge thanks to all the contributors to this release!

• Asim Shankar
• Ben Zinberg
• Billy Lamberta
• Brian Patton
• Christopher Suter
• Copybara-Service
• cyrilchimisov
• Dave Moore
• davmre
• Dustin Tran
• Ian Langmore
• jiamingz
• Jiaming Zeng
• Jonathan J Hunt
• Joshua V. Dillon
• Keyon Vafa
• Mark Daoust
• Matthew McAteer
• mgorinova
• mhoffman
• Michael Figurnov
• Mike Dusenberry
• rif
• saxeas
• srvasude
• William D. Irons
• yunhao

TensorFlow Probability 0.4.0-rc0

This is the 0th release candidate of the 0.4.0 release of TensorFlow Probability.

It is tested against TensorFlow v1.11.0

TensorFlow Probability 0.3.0

Release Notes

This is the 0.3.0 release of TensorFlow Probability. It's tested and stable against TensorFlow 1.10.

Distributions & Bijectors

• Add the LKJ distribution on correlation matrices.
• Add GammaGamma distribution.
• Adds the VonMisesFisher distribution over points on the unit hypersphere.
• Add CholeskyToInvCholesky bijector.
• Added reparametrizable TruncatedNormal
• Add tfp.bijectors.Transpose.
• Add tanh bijection.
• Introduce GaussianProcessRegressionModel
• Introduce GaussianProcess distribution
• Gamma distribution and the derived distributions (Beta, Dirichlet, Student's t, inverse Gamma) are fully reparameterized.
• Add low and high as properties to quantized distribution.
• Collapse WishartCholesky and WishartFull into a single Wishart distribution that takes either a scale or a scale_cholesky argument.
• Add adjoint arg to tfp.bijectors.Affine.

Sampling & Inference

• Enable nested interceptors in Edward2.
• Provide interface for controlling the number of HMC iterations during which to adapt the step size.
• Added support for dynamic shapes in the slice sampler.
• Make HMC more efficient and usable for MCEM.
  • Allow stop_gradient to be applied as new state is built (thus enabling recycling kernel_results.accepted.target_log_prob).
    • Add hook for user defined adaptive step size code and provide default implementation.
• Added implementation of the Nelder Mead derivative free optimization method.
• Add tfp.math.random_rayleigh.

Documentation & Examples

• Add Edward2 README.md.
• Add migration guide from Edward to TFP.
• Add documentation matching tfp-0.2 release.
• Add colab example which compares fitting HLM's between TF distributions, Stan, and R. Colab was written in collaboration with safyan@.
• Added a preliminary version of a Probabilistic PCA Edward 2 example, and changed the BUILD file accordingly.
• Latent Dirichlet Allocation for 20 newsgroups dataset.
• A detailed case study in using TensorFlow Probability for estimating a covariance matrix.

Huge thanks to all the contributors to this release!

• Akshay Agrawal
• Billy Lamberta
• Brian Patton
• Christopher Suter
• cyrilchimisov
• davmre
• Dustin Tran
• Ian Langmore
• jjhunt
• Joshua V. Dillon
• Kousuke Ariga
• Michael Figurnov
• Michele Colombo
• rif
• saxeas
• srvasude
• William D. Irons
• Yuan Huang

TensorFlow Probability 0.3.0-rc2

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 0.3.0-rc1

This is the rc1 release. We never actually build rc0, since we ended up advancing the branch state up to master (after some test fixes).

This release is tested against TensorFlow v1.10.0

TensorFlow Probability 0.3.0-rc0

This is the 0th release candidate of TensorFlow Probability version 0.3.0.

It's tested against TensorFlow 1.10.0

TensorFlow Probability 0.2.0

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

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

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.