Finding the M Most Probable Configurations Using Loopy Belief Propagation

@inproceedings{Yanover2003FindingTM,
  title={Finding the M Most Probable Configurations Using Loopy Belief Propagation},
  author={Chen Yanover and Yair Weiss},
  year={2003}
}
Loopy belief propagation (BP) has been successfully used in a number of difficult graphical models to find the most probable configuration of the hidden variables. In applications ranging from protein folding to image analysis one would like to find not just the best configuration but rather the top M . While this problem has been solved using the junction tree formalism, in many real world problems the clique size in the junction tree is prohibitively large. In this work we address the problem… CONTINUE READING
Highly Influential
This paper has highly influenced 12 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 121 citations. REVIEW CITATIONS

Citations

Publications citing this paper.
Showing 1-10 of 78 extracted citations

121 Citations

051015'06'09'12'15'18
Citations per Year
Semantic Scholar estimates that this publication has 121 citations based on the available data.

See our FAQ for additional information.

References

Publications referenced by this paper.
Showing 1-10 of 20 references

An efficient algorithm for finding the M most probable configurations in probabilistic expert systems

D. Nilsson
Statistics and Computing, • 1998
View 9 Excerpts
Highly Influenced

Understanding belief propagation and its generalizations

J. Yedidia, W. Freeman, Y. Weiss
2003
View 1 Excerpt

The bayes net toolbox for matlab

Kevin Murphy
Computing Science and Statistics, • 2001
View 1 Excerpt

Similar Papers

Loading similar papers…