Occam factors and model independent Bayesian learning of continuous distributions.
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Stereotypical Escape Behavior in Caenorhabditis elegans Allows Quantification of Effective Heat Stimulus LevelInformation transduction capacity of noisy biochemical signaling networksNeural coding of natural stimuli: information at sub-millisecond resolution.Bayesian Uncertainty Quantification for Bond Energies and Mobilities Using Path Integral Analysis.Encoding uncertainty in the hippocampus.Unification of field theory and maximum entropy methods for learning probability densities.Bayesian Feature Selection with Strongly Regularizing Priors Maps to the Ising Model.Bayesian feature selection for high-dimensional linear regression via the Ising approximation with applications to genomics.Estimation of probability densities using scale-free field theories.Fluctuation-dissipation theorem and models of learning.Estimating instantaneous irregularity of neuronal firing.
P2860
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P2860
Occam factors and model independent Bayesian learning of continuous distributions.
description
2002 nî lūn-bûn
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2002年の論文
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2002年学术文章
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2002年学术文章
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2002年学术文章
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2002年学术文章
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2002年学术文章
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2002年學術文章
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name
Occam factors and model independent Bayesian learning of continuous distributions.
@en
Occam factors and model independent Bayesian learning of continuous distributions.
@nl
type
label
Occam factors and model independent Bayesian learning of continuous distributions.
@en
Occam factors and model independent Bayesian learning of continuous distributions.
@nl
prefLabel
Occam factors and model independent Bayesian learning of continuous distributions.
@en
Occam factors and model independent Bayesian learning of continuous distributions.
@nl
P2860
P1433
P1476
Occam factors and model independent Bayesian learning of continuous distributions.
@en
P2093
William Bialek
P2860
P304
P356
10.1103/PHYSREVE.65.026137
P407
P433
P577
2002-01-24T00:00:00Z
P698
P818
cond-mat/0009165