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Maximum Entropy and Bayesian Methods

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Cover of 'Maximum Entropy and Bayesian Methods'

Table of Contents

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    Book Overview
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    Chapter 1 Flow and Diffusion Images from Bayesian Spectral Analysis of Motion-Encoded NMR Data
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    Chapter 2 Bayesian Estimation of MR Images from Incomplete Raw Data
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    Chapter 3 Quantified Maximum Entropy and Biological EPR Spectra
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    Chapter 4 The Vital Importance of Prior Information for the Decomposition of Ion Scattering Spectroscopy Data
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    Chapter 5 Bayesian Consideration of the Tomography Problem
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    Chapter 6 Using MaxEnt to Determine Nuclear Level Densities
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    Chapter 7 A Fresh Look at Model Selection in Inverse Scaterring
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    Chapter 8 The Maximum-Entropy Method in Small-Angle Scattering
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    Chapter 9 Maximum Entropy Multi-Resolution EM Tomography by Adaptive Subdivision
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    Chapter 10 High Resolution Image Construction from IRAS Survey — Parallelization and Artifact Suppression
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    Chapter 11 Maximum Entropy Performance Analysis Of Spread-Spectrum Multiple-Access Communications
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    Chapter 12 Noise Analysis in Optical Fibre Sensing: A Study using the Maximum Entropy Method
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    Chapter 13 Autoclass — A Bayesian Approach to Classification
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    Chapter 14 Evolution Review Of BayesCalc, A Mathematica ™ Package for doing Bayesian Calculations
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    Chapter 15 Bayesian Inference for Basis Function Selection in Nonlinear System Identification using Genetic Algorithms
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    Chapter 16 The meaning of the word “Probability”
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    Chapter 17 The Hard Truth
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    Chapter 18 Are the Samples Doped — If so, How Much?
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    Chapter 19 Confidence Intervals from one Observation
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    Chapter 20 Hyothesis Refinement
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    Chapter 21 Bayesian Density Estimation
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    Chapter 22 Scale Invariant Markov Models for Bayesian Inversion of Linear Inverse Problems
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    Chapter 23 Foundations: Indifference, Independence & MaxEnt
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    Chapter 24 The Maximum Entropy on the Mean Method, Noise and Sensitivity
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    Chapter 25 The Maximum Entropy Algorithm Applied to the Two-Dimensional Random Packing Problem
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    Chapter 26 Bayesian Comparison of Models for Images
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    Chapter 27 Interpolation Models with Multiple Hyperparameters
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    Chapter 28 Density Networks and their Application to Protein Modelling
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    Chapter 29 The Cluster Expansion: A Hierarchical Density Model
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    Chapter 30 The Partitioned Mixture Distribution: Multiple Overlapping Density Models
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    Chapter 31 Generating Functional for the BBGKY Hierarchy and the N-Identical-Body Problem
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    Chapter 32 Entropies for Continua: Fluids and Magnetofluids
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    Chapter 33 A Logical Foundation for Real Thermodynamics
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Title
Maximum Entropy and Bayesian Methods
Published by
Springer Netherlands, December 2012
DOI 10.1007/978-94-009-0107-0
ISBNs
978-9-40-106534-4, 978-9-40-090107-0
Editors

Skilling, John, Sibisi, Sibusiso

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