Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
93 tokens/sec
Gemini 2.5 Pro Premium
54 tokens/sec
GPT-5 Medium
22 tokens/sec
GPT-5 High Premium
17 tokens/sec
GPT-4o
101 tokens/sec
DeepSeek R1 via Azure Premium
91 tokens/sec
GPT OSS 120B via Groq Premium
441 tokens/sec
Kimi K2 via Groq Premium
225 tokens/sec
2000 character limit reached

An Axiomatic Framework for Bayesian and Belief-function Propagation (1304.2374v1)

Published 27 Mar 2013 in cs.AI

Abstract: In this paper, we describe an abstract framework and axioms under which exact local computation of marginals is possible. The primitive objects of the framework are variables and valuations. The primitive operators of the framework are combination and marginalization. These operate on valuations. We state three axioms for these operators and we derive the possibility of local computation from the axioms. Next, we describe a propagation scheme for computing marginals of a valuation when we have a factorization of the valuation on a hypertree. Finally we show how the problem of computing marginals of joint probability distributions and joint belief functions fits the general framework.

Citations (40)

Summary

We haven't generated a summary for this paper yet.

Dice Question Streamline Icon: https://streamlinehq.com

Follow-up Questions

We haven't generated follow-up questions for this paper yet.