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Maximum Entropy and Bayesian Methods

Kenneth M. Hanson · 1996

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About the book

This volume contains the proceedings of the <em>Fifteenth International</em> <em>Workshop on Maximum Entropy and Bayesian Methods</em>, held in Sante Fe, New Mexico, USA, from July 31 to August 4, 1995. <br/> Maximum entropy and Bayesian methods are widely applied to statistical data analysis and scientific inference in the natural and social sciences, engineering and medicine. Practical applications include, among others, parametric model fitting and model selection, ill-posed inverse problems, image reconstruction, signal processing, decision making, and spectrum estimation. Fundamental applications include the common foundations for statistical inference, statistical physics and information theory. Specific sessions during the workshop focused on time series analysis, machine learning, deformable geometric models, and data analysis of Monte Carlo simulations, as well as reviewing the relation between maximum entropy and information theory. <br/> <em>Audience:</em> This book should be of interest to scientists, engineers, medical professionals, and others engaged in such topics as data analysis, statistical inference, image processing, and signal processing.

Book details

Year
1996
Language
English
Series
Fundamental Theories of Physics, An International Book Series on The Fundamental Theories of Physics: Their Clarificatio
Publisher
Springer Netherlands
Editions
3
Pages
480
ISBN
9789401154307

Data source: Wikidata

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