Maximum Entropy and Bayesian Methods.

Abstract

This volume contains selections from among the presentations at the Thirteenth International Workshop on Maximum Entropy and Bayesian Methods- MAXENT93 for short- held at the University of California, Santa Barbara (UCSB), August 1-5, 1993. This annual workshop is devoted to the theory and practice of Bayesian probability and the use of the maximum entropy principle in assigning prior probabilities. Like its predecessors, MAXENT93 attracted researchers and scholars representing a wide diversity of disciplines and applications. These included physicists, geophysicists, astronomers, statisticians, engineers, and economists, among others. Indeed Bayesian methods increasingly compel the interest of any who would apply scientific inference. The impressive successes, so evident in the proceedings of the past workshops, when adherence to Bayesian principles replaces popular ad hoc approaches in problems of inference, continue. Many are reported in this volume. It is perhaps indicative of the growing acceptance of Bayesian methods that the most prominent controversy at the thirteenth workshop was not a Bayesian- frequents confrontation but rather a disagreement over the suitability of using an approximation in the Bayesian formalism.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1996
Accession Number
ADA312364

Entities

People

  • Glenn R. Heidbreder
  • Hua Lee

Organizations

  • University of California, Santa Barbara

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors
  • Weapons Technologies

DTIC Thesaurus Topics

  • Bayesian Networks
  • Birds
  • Computational Science
  • Computer Programming
  • Data Mining
  • Databases
  • Gaussian Distributions
  • Information Processing
  • Information Science
  • Information Systems
  • Monte Carlo Method
  • Network Science
  • Probabilistic Models
  • Quantum Mechanics
  • Statistical Algorithms
  • Surveys
  • Three Dimensional

Readers

  • Academic Conference Management
  • Artificial Intelligence
  • Theoretical Analysis.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference