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TensorFlow Probability 0.19.0

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@emilyfertig emilyfertig released this 06 Dec 22:34
0759c57

Release notes

This is the 0.19.0 release of TensorFlow Probability. It is tested and stable against TensorFlow version 2.11 and JAX 0.3.25 .

Change notes

  • Bijectors

    • Added UnitVector bijector to map to the unit sphere.
  • Distributions

    • Added noncentral Chi2 distribution to TFP.
    • Added differentiable quantile and cdf function approximation to NC2 distribution.
    • Added quantiles to Student-T, Beta and SigmoidBeta, with efficient
      implementations for Student-T quantile/cdf.
    • Allow structured index points to GaussianProcess* classes.
    • Improved efficiency of GaussianProcess* gradients through custom gradients
      on log_prob.
  • Linear Algebra

    • Added functions (with custom gradients) to handle Hermitian Symmetric Positive-definite matrices:
      • tfp.math.hspd_logdet
      • tfp.math.hpsd_quadratic_form_solve and tfp.math.hpsd_quadratic_form_solvevec
      • tfp.math.hpsd_solve and tfp.math.hpsd_solvevec
  • Optimizer

    • BUGFIX: Prevent Hager-Zhang linesearch from terminating early.
  • PSD Kernels

    • Added support for structured inputs in PSD Kernel.
  • STS

    • Added seasonality support to STS Gibbs Sampler.
  • Other

    • BUGFIX: Allow jnp.bfloat16 arrays to be correctly recognized as floats.

Huge thanks to all the contributors to this release!

  • Brian Patton
  • Chen Qian
  • Christopher Suter
  • Colin Carrol
  • Emily Fertig
  • Francois Chollet
  • Ian Langmore
  • Jacob Burnim
  • Jonas Eschle
  • Kyle Loveless
  • Leandro Campos
  • Du Phan
  • Pavel Sountsov
  • Sebastian Nowozin
  • Srinivas Vasudevan
  • Thomas Colthurst
  • Umer Javed
  • Urs Koster
  • Yash Katariya