Titlebook: Maximum Entropy and Bayesian Methods Santa Barbara, California, U.S.A., 1993; Glenn R. Heidbreder Book 1996 Springer Science+Business Medi

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Biomarker

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Hyperparameters: Optimize, or Integrate Out?ficant biases to arise in the MAP method. In contrast, the evidence framework is shown to introduce negligible predictive error, under straightforward conditions..General lessons are drawn concerning the distinctive properties of inference in many dimensions.

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Bayesian Robustness: A New Look from Geometryults are then applied to the class of entropic priors. It is shown that the hyper parameter controls the sensitivity with respect to local deformations. It is also shown that entropic priors are only sensitive to deformations that change the intrinsic form of the model around the initial guess.

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Nibble

liposuction

Maximum Entropy Signal Transmissionrthquakes. Another example is passive sonar where engine noise from a hidden submarine is used to locate its position. In the typical inverse medium problem the source of energy (usually man-made) is local, the signal penetrates an inaccessible medium that reflects energy back to accessible points,

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