Using Autodiff to Estimate Posterior Moments, Marginals and Samples: Derivations

Written by bayesianinference | Published 2024/04/15
Tech Story Tags: autodiff | estimate-posterior-moments | importance-weighting | bayesian-posterior | reweight-samples | conditional-independencies | importance-sampling | backward-traversals

TLDRImportance weighting allows us to reweight samples drawn from a proposal in order to compute expectations of a different distribution.via the TL;DR App

This paper is available on arxiv under CC 4.0 license.

Authors:

(1) Sam Bowyer, Equal contribution, Department of Mathematics and [email protected];

(2) Thomas Heap, Equal contribution, Department of Computer Science University of Bristol and [email protected];

(3) Laurence Aitchison, Department of Computer Science University of Bristol and [email protected].

Table of Links

Derivations

Global Importance Sampling

Massively Parallel Importance Sampling


Written by bayesianinference | At BayesianInference.Tech, as more evidence becomes available, we make predictions and refine beliefs.
Published by HackerNoon on 2024/04/15