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Maximum Entropy and Bayesian Methods

Santa Fe, New Mexico, U.S.A., 1995 Proceedings of the Fifteenth International Workshop on Maximum Entropy and Bayesian Methods

  • Conference proceedings
  • © 1996

Overview

Editors:
  1. Kenneth M. Hanson

    1. Dynamic Experimentation Division, Los Alamos National Laboratory, Los Alamos, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Richard N. Silver

    1. Theoretical Division, Los Alamos National Laboratory, Los Alamos, USA

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Fundamental Theories of Physics (FTPH, volume 79)

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Table of contents (57 papers)

  1. Front Matter

    Pages i-xxii
    Download chapter PDF

  2. Reconstruction of the Probability Density Function Implicit in Option Prices from Incomplete and Noisy Data

    • R. J. Hawkins, M. Rubinstein, G. J. Daniell
    Pages 1-8

  3. Model Selection and Parameter Estimation for Exponential Signals

    • Anand Ramaswami, G. Larry Bretthorst
    Pages 9-14

  4. Hierarchical Bayesian Time Series Models

    • L. Mark Berliner
    Pages 15-22

  5. Bayesian Time Series: Models and Computations for the Analysis of Time Series in the Physical Sciences

    • Mike West
    Pages 23-34

  6. Maxent, Mathematics, and Information Theory

    • I. Csiszár
    Pages 35-50

  7. Bayesian Estimation of the Von Mises Concentration Parameter

    • D. L. Dowe, J. J. Oliver, R. A. Baxter, C. S. Wallace
    Pages 51-60

  8. A Characterization of the Dirichlet Distribution with Application to Learning Bayesian Networks

    • Dan Geiger, David Heckerman
    Pages 61-68

  9. The Bootstrap is Inconsistent with Probability Theory

    • David H. Wolpert
    Pages 69-76

  10. Data-Driven Priors for Hyperparameters in Regularization

    • Daniel Keren, Michael Werman
    Pages 77-84

  11. Mixture Modeling to Incorporate Meaningful Constraints into Learning

    • I. Tchoumatchenko, J.-G. Ganascia
    Pages 85-92

  12. Maximum Entropy (Maxent) Method in Expert Systems and Intelligent Control: New Possibilities and Limitations

    • V. Kreinovich, H. T. Nguyen, E. A. Walker
    Pages 93-100

  13. The De Finetti Transform

    • S. James Press
    Pages 101-108

  14. Continuum Models for Bayesian Image Matching

    • J. C. Gee, P. D. Peralta
    Pages 109-116

  15. Mechanical Models as Priors in Bayesian Tomographic Reconstruction

    • Anand Rangarajan, Soo-Jin Lee, Gene Gindi
    Pages 117-124

  16. The Bayes Inference Engine

    • K. M. Hanson, G. S. Cunningham
    Pages 125-134

  17. A Full Bayesian Approach for Inverse Problems

    • Ali Mohammad-Djafari
    Pages 135-144

  18. Pixon-Based Multiresolution Image Reconstruction and Quantification of Image Information Content

    • R. C. Puetter
    Pages 145-152

  19. Bayesian Multimodal Evidence Computation by Adapti Tempering MCMC

    • Miao-Dan Wu, William J. Fitzgerald
    Pages 153-162

  20. Bayesian Inference and the Analytic Continuation of Imaginary-Time Quantum Monte Carlo Data

    • J. E. Gubernatis, J. Bonča, Mark Jarrell
    Pages 163-170
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Keywords

Editors and Affiliations

  • Dynamic Experimentation Division, Los Alamos National Laboratory, Los Alamos, USA

    Kenneth M. Hanson

  • Theoretical Division, Los Alamos National Laboratory, Los Alamos, USA

    Richard N. Silver

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