Factor graph fragmentization of expectation propagation
نویسندگان
چکیده
منابع مشابه
Expectation Propagation in Factor Graphs: A Tutorial
Expectation propagation is an important variational inference algorithm for graphical models, especially if some of the variables are continuous. This tutorial presents two views EP: as repeatedly projecting into an approximating family, and as a message-passing algorithm. We present EP in terms of factor graphs, which simplifies some of the presentation and provides concreteness, while remaini...
متن کاملImproving on Expectation Propagation
A series of corrections is developed for the fixed points of Expectation Propagation (EP), which is one of the most popular methods for approximate probabilistic inference. These corrections can lead to improvements of the inference approximation or serve as a sanity check, indicating when EP yields unrealiable results.
متن کاملSelf-Averaging Expectation Propagation
We investigate the problem of approximate Bayesian inference for a general class of observation models by means of the expectation propagation (EP) framework for large systems under some statistical assumptions. Our approach tries to overcome the numerical bottleneck of EP caused by the inversion of large matrices. Assuming that the measurement matrices are realizations of specific types of ens...
متن کاملExpectation Particle Belief Propagation
We propose an original particle-based implementation of the Loopy Belief Propagation (LPB) algorithm for pairwise Markov Random Fields (MRF) on a continuous state space. The algorithm constructs adaptively efficient proposal distributions approximating the local beliefs at each note of the MRF. This is achieved by considering proposal distributions in the exponential family whose parameters are...
متن کاملStochastic Expectation Propagation
Expectation propagation (EP) is a deterministic approximation algorithm that is often used to perform approximate Bayesian parameter learning. EP approximates the full intractable posterior distribution through a set of local approximations that are iteratively refined for each datapoint. EP can offer analytic and computational advantages over other approximations, such as Variational Inference...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Korean Statistical Society
سال: 2020
ISSN: 1226-3192,2005-2863
DOI: 10.1007/s42952-019-00033-9