Gaussian sampling by local perturbations

@inproceedings{Papandreou2010GaussianSB,
  title={Gaussian sampling by local perturbations},
  author={George Papandreou and Alan Loddon Yuille},
  booktitle={NIPS},
  year={2010}
}
We present a technique for exact simulation of Gaussian Markov random fields (GMRFs), which can be interpreted as locally injecting noise to each Gaussian factor independently, followed by computing the mean/mode of the perturbed GMRF. Coupled with standard iterative techniques for the solution of symmetric positive definite systems, this yields a very efficient sampling algorithm with essentially linear complexity in terms of speed and memory requirements, well suited to extremely large scale… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 37 REFERENCES

Multiresolution Markov models for signal and image processing

  • A. Willsky
  • Proc. IEEE, 90(8):1396– 1458,
  • 2002
Highly Influential
10 Excerpts

Scale mixtures of normal distributions

  • D. Andrews, C. Mallows
  • JRSS (B), 36(1):99–102,
  • 1974
Highly Influential
7 Excerpts

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