A Linear Approximation Method for Probabilistic Inference
Artificial Intelligence
2013-04-10 v1
Abstract
An approximation method is presented for probabilistic inference with continuous random variables. These problems can arise in many practical problems, in particular where there are "second order" probabilities. The approximation, based on the Gaussian influence diagram, iterates over linear approximations to the inference problem.
Cite
@article{arxiv.1304.2373,
title = {A Linear Approximation Method for Probabilistic Inference},
author = {Ross D. Shachter},
journal= {arXiv preprint arXiv:1304.2373},
year = {2013}
}
Comments
Appears in Proceedings of the Fourth Conference on Uncertainty in Artificial Intelligence (UAI1988)