Corpus ID: 918975

Symmetry-Aware Marginal Density Estimation

@article{Niepert2013SymmetryAwareMD,
  title={Symmetry-Aware Marginal Density Estimation},
  author={Mathias Niepert},
  journal={ArXiv},
  year={2013},
  volume={abs/1304.2694}
}
  • Mathias Niepert
  • Published 2013
  • Computer Science
  • ArXiv
  • The Rao-Blackwell theorem is utilized to analyze and improve the scalability of inference in large probabilistic models that exhibit symmetries. A novel marginal density estimator is introduced and shown both analytically and empirically to outperform standard estimators by several orders of magnitude. The developed theory and algorithms apply to a broad class of probabilistic models including statistical relational models considered not susceptible to lifted probabilistic inference. 
    20 Citations

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