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Advanced Methodologies for Bayesian Networks

reviewed and selected from numerous submissions. In the International Workshop on Advanced Methodologies for Bayesian Networks (AMBN), the;

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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Modeling and Reasoning with Bayesian Networks

This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive;

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Bayesian Artificial Intelligence

classifiers New section on object-oriented Bayesian networks New section that addresses foundational problems with causal discovery and Markov blanket;

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Bayesian Artificial Intelligence

errors New applications and case studies More coverage on the uses of causal interventions to understand and reason with causal Bayesian;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling;

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Development of Clinical Decision Support Systems using Bayesian Networks

: in modeling and validation of workflows, guided modeling, semi-automated modeling, advanced Bayesian networks, model-user interaction, inter;

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty

This book constitutes the refereed proceedings of the 14th European Conference on Symbolic and Quantitative Approaches to Reasoning with;

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Probabilistic Methods for Bioinformatics

The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability;

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Machine Learning

machines, Bayesian inference with a focus on the EM algorithm and its approximate inference variational versions, Monte Carlo methods;

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Probabilistic Reasoning in Multiagent Systems

probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an;

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Probabilistic Reasoning in Multiagent Systems

probabilistic reasoning. Probabilistic reasoning with graphical models, also known as Bayesian networks or belief networks, has become increasingly an;

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Bayesian Analysis in Natural Language Processing

grammar modeling, neural networks and representation learning, and their use with Bayesian analysis.;

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Bayesian Networks for Reliability Engineering

This book presents a bibliographical review of the use of Bayesian networks in reliability over the last decade. Bayesian network (BN;

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Advances in Artificial Intelligence

papers are organized in topical sections on Bayesian networks and uncertainty modeling; fuzzy logic and soft computing; knowledge representation;

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Bayesian Networks and Influence Diagrams

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Bayesian Modeling in Bioinformatics

Bayesian Modeling in Bioinformatics discusses the development and application of Bayesian statistical methods for the analysis of high;

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Bayesian Psychometric Modeling

Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book introduces;

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Bayesian Psychometric Modeling

using Bayesian methods and why many of the activities in psychometrics align with Bayesian thinking. The first part of the book;

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Bayesian Programming

of Bayesian programming, the main probabilistic models, general purpose algorithms for Bayesian inference, and learning problems. FAQsAlong with a;

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Bayesian Programming

of Bayesian programming, the main probabilistic models, general purpose algorithms for Bayesian inference, and learning problems. FAQsAlong with a;

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Bayesian Networks for Managing Learner Models in Adaptive Hypermedia Systems

Teachers use e-learning systems to develop course notes and web-based activities to communicate with learners on one side and monitor and;

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Benefits of Bayesian Network Models

The application of Bayesian Networks (BN) or Dynamic Bayesian Networks (DBN) in dependability and risk analysis is a recent development. A;

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Essential Bayesian Models

of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric;

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Bayesian Modeling Using WinBUGS

implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key;

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