£118.63

Springer Maximum Entropy and Bayesian Methods - Vol 105

Name: Springer Maximum Entropy and Bayesian Methods - Vol 105
Brand: Springer
Price: 118.63 GBP
Availability: InStock

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Description

Explore the advanced concepts of probability theory with this volume from the Fundamental Theories of Physics series. This book contains the proceedings from the 18th International Workshop on Maximum Entropy and Bayesian Methods held in Garching, Germany in 1998. Since the series was initiated by Edwin T. Jaynes and Myron Tribus, these workshops have provided a dedicated space for exchanging ideas regarding technical aspects and applications of Bayesian probability. What began in 1981 has evolved from focusing on fundamental concepts into addressing increasingly realistic and challenging applications. This collection serves as a vital resource for those studying computer science, AI, and machine learning. It captures the progression of the workshop's focus, offering insights into how Bayesian theory is applied to complex real-world scenarios. Whether you are a researcher or a student, this Springer publication provides a deep look into the developments that have shaped the field over nearly two decades of international collaboration.

Key Features

Contains full proceedings from the 18th International Workshop held in Garching, Germany.

Part of the Fundamental Theories of Physics series, specifically volume 105.

Covers a wide range of technical aspects and applications of Bayesian probability theory.

Tracks the evolution of the field from fundamental concepts to modern, challenging applications.

Published by Springer, a trusted name in scientific and academic literature.

Provides a historical and technical record of developments in maximum entropy methods.

Product Specifications

Brand: Springer
Format: hardcover
ASIN: 0792357663
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 31 July 1999
Listed Since: 15 December 2006

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Springer Maximum Entropy and Bayesian Methods - Vol 105

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