Maximum Entropy and Bayesian Methods

Boise, Idaho, USA, 1997 Proceedings of the 17th International Workshop on Maximum Entropy and Bayesian Methods of Statistical Analysis

  • Gary J. Erickson
  • Joshua T. Rychert
  • C. Ray Smith
Conference proceedings

Part of the Fundamental Theories of Physics book series (FTPH, volume 98)

Table of contents

  1. Front Matter
    Pages i-ix
  2. John Skilling
    Pages 1-14
  3. Carlos C. Rodriguez
    Pages 15-24
  4. D. E. Cooke, V. Kreinovich, L. Longpré
    Pages 25-33
  5. Ali Mohammad-Djafari
    Pages 57-69
  6. Anthony J. M. Garrett
    Pages 71-86
  7. W. Von Der Linden, V. Dose, A. Ramaswami
    Pages 87-99
  8. Anthony J. M. Garrett
    Pages 115-120
  9. K. M. Hanson, G. S. Cunningham, S. S. Saquib
    Pages 121-135
  10. R. Preuss, V. Dose, W. Von Der Linden
    Pages 137-145
  11. V. Dose, R. Fischer, W. von der Linden
    Pages 147-152
  12. Amit Chakraborty, James S. Duncan
    Pages 171-182
  13. J. C. Gee, L. Le Briquer
    Pages 199-207
  14. Anthony J. M. Garrett
    Pages 223-238
  15. D. Fox, M. Schmidt, M. Koshelev, V. Kreinovich, L. Longpré, J. Kuhn
    Pages 239-251
  16. Holly E. Fitzgerald, Everett G. Larson
    Pages 263-269
  17. R. Osegueda, C. Ferregut, M. J. George, J. M. Gutierrez, V. Kreinovich
    Pages 277-289
  18. Henryk Gzyl
    Pages 291-294
  19. Back Matter
    Pages 295-302

About these proceedings


This volume has its origin in the Seventeenth International Workshop on Maximum Entropy and Bayesian Methods, MAXENT 97. The workshop was held at Boise State University in Boise, Idaho, on August 4 -8, 1997. As in the past, the purpose of the workshop was to bring together researchers in different fields to present papers on applications of Bayesian methods (these include maximum entropy) in science, engineering, medicine, economics, and many other disciplines. Thanks to significant theoretical advances and the personal computer, much progress has been made since our first Workshop in 1981. As indicated by several papers in these proceedings, the subject has matured to a stage in which computational algorithms are the objects of interest, the thrust being on feasibility, efficiency and innovation. Though applications are proliferating at a staggering rate, some in areas that hardly existed a decade ago, it is pleasing that due attention is still being paid to foundations of the subject. The following list of descriptors, applicable to papers in this volume, gives a sense of its contents: deconvolution, inverse problems, instrument (point-spread) function, model comparison, multi sensor data fusion, image processing, tomography, reconstruction, deformable models, pattern recognition, classification and group analysis, segmentation/edge detection, brain shape, marginalization, algorithms, complexity, Ockham's razor as an inference tool, foundations of probability theory, symmetry, history of probability theory and computability. MAXENT 97 and these proceedings could not have been brought to final form without the support and help of a number of people.


Experiment Maximum entropy method Potential Probability theory algorithms bayesian statistics best fit coding theory image processing information information theory machine learning statistics uncertainty

Editors and affiliations

  • Gary J. Erickson
    • 1
  • Joshua T. Rychert
    • 1
  • C. Ray Smith
    • 2
  1. 1.Department of Electronical EngineeringBoise State UniversityBoiseUSA
  2. 2.FayettevilleUSA

Bibliographic information