Module: tf.contrib.bayesflow.monte_carlo
Stay organized with collections
Save and categorize content based on your preferences.
Monte Carlo integration and helpers.
Use tfp.monte_carlo instead.
Functions
expectation(...): Computes the Monte-Carlo approximation of \(E_p[f(X)]\). (deprecated)
expectation_importance_sampler(...): Monte Carlo estimate of \(E_p[f(Z)] = E_q[f(Z) p(Z) / q(Z)]\).
expectation_importance_sampler_logspace(...): Importance sampling with a positive function, in log-space.
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2020-10-01 UTC.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[]]
View source on GitHub