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Research Article

A Trick for Computing Expected Values in High-Dimensional Probabilistic Models

Pages 126-132 | Accepted 28 Oct 2011, Published online: 07 Dec 2011

References

  • Ahmadian Y, Pillow JW, Paninski L. Efficient Markov chain Monte Carlo methods for decoding neural spike trains. Neural Computation 2011; 23: 46–96
  • Lehmann EL, Casella G. Theory of point estimation. Springer, New York 1998
  • Pouget A, Dayan P, Zemel RS. Inference and computation with population codes. Annual Review of Neuroscience 2003; 26: 381–410
  • Robert C, Casella G. Monte Carlo Statistical Methods. Springer, New York 2005
  • Yaeli S, Meir R. Error-based analysis of optimal tuning functions explains phenomena observed in sensory neurons. Frontiers in Computational Neuroscience 2010; 4: 130

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