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  • Conference proceedings
  • © 1996

Maximum Entropy and Bayesian Methods

Cambridge, England, 1994 Proceedings of the Fourteenth International Workshop on Maximum Entropy and Bayesian Methods

Part of the book series: Fundamental Theories of Physics (FTPH, volume 70)

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Table of contents (33 papers)

  1. Front Matter

    Pages i-xi
  2. Applications

    1. Flow and Diffusion Images from Bayesian Spectral Analysis of Motion-Encoded NMR Data

      • E. J. Fordham, D. Xing, J. A. Derbyshire, S. J. Gibbs, T. A. Carpenter, L. D. Hall
      Pages 1-12
    2. Bayesian Estimation of MR Images from Incomplete Raw Data

      • G. J. Marseille, R. de Beer, M. Fuderer, A. F. Mehlkopf, D. van Ormondt
      Pages 13-22
    3. Quantified Maximum Entropy and Biological EPR Spectra

      • S. M. Glidewell, B. A. Goodman, J. Skilling
      Pages 23-30
    4. Bayesian Consideration of the Tomography Problem

      • W. von der Linden, K. Ertl, V. Dose
      Pages 41-49
    5. Using MaxEnt to Determine Nuclear Level Densities

      • N. J. Davidson, B. J. Cole, H. G. Miller
      Pages 51-58
    6. A Fresh Look at Model Selection in Inverse Scaterring

      • Vincent A. Macaulay, Brian Buck
      Pages 59-67
    7. The Maximum-Entropy Method in Small-Angle Scattering

      • Steen Hansen, Jürgen J. Müller
      Pages 69-78
    8. Maximum Entropy Multi-Resolution EM Tomography by Adaptive Subdivision

      • Li-He Zou, Zhengrong Wang, Louis E. Roemer
      Pages 79-89
    9. Maximum Entropy Performance Analysis Of Spread-Spectrum Multiple-Access Communications

      • F. Solms, P. G. W. van Rooyen, J. S. Kunicki
      Pages 101-108
    10. Noise Analysis in Optical Fibre Sensing: A Study using the Maximum Entropy Method

      • L. Stergioulas, A. Vourdas, G. R. Jones
      Pages 109-116
  3. Algorithms

    1. Autoclass — A Bayesian Approach to Classification

      • John Stutz, Peter Cheeseman
      Pages 117-126
    2. Evolution Review Of BayesCalc, A Mathematica™ Package for doing Bayesian Calculations

      • Paul Desmedt, Ignace Lemahieu, K. Thielemans
      Pages 127-134
    3. The meaning of the word “Probability”

      • Myron Tribus
      Pages 143-155
    4. The Hard Truth

      • Kenneth M. Hanson, Gregory S. Cunningham
      Pages 157-164
    5. Are the Samples Doped — If so, How Much?

      • Anthony J. M. Garrett
      Pages 165-174
    6. Confidence Intervals from one Observation

      • C. C. Rodríguez
      Pages 175-182

About this book

This volume records papers given at the fourteenth international maximum entropy conference, held at St John's College Cambridge, England. It seems hard to believe that just thirteen years have passed since the first in the series, held at the University of Wyoming in 1981, and six years have passed since the meeting last took place here in Cambridge. So much has happened. There are two major themes at these meetings, inference and physics. The inference work uses the confluence of Bayesian and maximum entropy ideas to develop and explore a wide range of scientific applications, mostly concerning data analysis in one form or another. The physics work uses maximum entropy ideas to explore the thermodynamic world of macroscopic phenomena. Of the two, physics has the deeper historical roots, and much of the inspiration behind the inference work derives from physics. Yet it is no accident that most of the papers at these meetings are on the inference side. To develop new physics, one must use one's brains alone. To develop inference, computers are used as well, so that the stunning advances in computational power render the field open to rapid advance. Indeed, we have seen a revolution. In the larger world of statistics beyond the maximum entropy movement as such, there is now an explosion of work in Bayesian methods, as the inherent superiority of a defensible and consistent logical structure becomes increasingly apparent in practice.

Keywords

  • Markov model
  • Probability theory
  • classification
  • image processing
  • maximum entropy method
  • neural networks
  • thermodynamics

Editors and Affiliations

  • Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, England

    John Skilling, Sibusiso Sibisi

Bibliographic Information

Buying options

eBook USD 169.00
Price excludes VAT (USA)
  • ISBN: 978-94-009-0107-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 219.99
Price excludes VAT (USA)
Hardcover Book USD 249.00
Price excludes VAT (USA)