Belief propagation for networks with loops
نویسندگان
چکیده
A novel belief propagation algorithm is derived for the solution of probabilistic models on networks containing short loops.
منابع مشابه
Exactness of Belief Propagation for some Graphical Models with Loops
It is well known that an arbitrary discrete-variable graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by algorithms of the Belief Propagation (BP) type. Extending recent results of Kolmogorov & Wainwright ’05 and Bayati, Shah, & Sharma ’06, we discuss here two cases of the opposite extreme, when BP algorithm finds optim...
متن کاملOn the convergence of belief propagation algorithm for stochastic networks with loops
The belief propagation (BP) algorithm is a tool with which one can calculate beliefs, marginal probabilities, of stochastic networks without loops (e.g., Bayesian networks) in a time proportional to the number of nodes. For networks with loops, it may not converge and, even if it converges, beliefs may not equal to exact marginal probabilities although its application is known to give remarkabl...
متن کاملZooBP: Belief Propagation for Heterogeneous Networks
Given a heterogeneous network, with nodes of di↵erent types – e.g., products, users and sellers from an online recommendation site like Amazon – and labels for a few nodes (‘honest’, ‘suspicious’, etc), can we find a closed formula for Belief Propagation (BP), exact or approximate? Can we say whether it will converge? BP, traditionally an inference algorithm for graphical models, exploits so-ca...
متن کاملExactness of Belief Propagation in the Zero Temperature Limit for Some Graphical Models with Loops
It is well known that an arbitrary graphical model of statistical inference defined on a tree, i.e. on a graph without loops, is solved exactly and efficiently by an iterative Belief Propagation (BP) algorithm convergent to unique minimum of the so-called Bethe free energy functional. For a general graphical model on a loopy graph the functional may show multiple minima, the iterative BP algori...
متن کاملBelief Propagation with Strings
Strings and string operations are very widely used, particularly in applications that involve text, speech or sequences. Yet the vast majority of probabilistic models contain only numerical random variables, not strings. In this paper, we show how belief propagation can be applied to do inference in models with string random variables which use common string operations like concatenation, find/...
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: Science Advances
سال: 2021
ISSN: ['2375-2548']
DOI: https://doi.org/10.1126/sciadv.abf1211