Random variable transformations
Random variable transformations (contrib)
Bijector Ops.
An API for invertible, differentiable transformations of random variables.
Background
Differentiable, bijective transformations of continuous random variables alter the calculations made in the cumulative/probability distribution functions and sample function. This module provides a standard interface for making these manipulations.
For more details and examples, see the Bijector
docstring.
To apply a Bijector
, use distributions.TransformedDistribution
.
Bijectors
tf-contrib-distributions-bijector-Affine
tf.contrib.distributions.bijector.AffineLinearOperator
tf-contrib-distributions-bijector-Bijector
tf.contrib.distributions.bijector.Chain
tf-contrib-distributions-bijector-CholeskyOuterProduct
tf.contrib.distributions.bijector.Exp
tf-contrib-distributions-bijector-Identity
tf.contrib.distributions.bijector.Inline
tf-contrib-distributions-bijector-Invert
tf.contrib.distributions.bijector.PowerTransform
tf-contrib-distributions-bijector-SigmoidCentered
tf.contrib.distributions.bijector.SoftmaxCentered
tf-contrib-distributions-bijector-Softplus
© 2017 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/api_guides/python/contrib.distributions.bijector