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Author:   Marloes Maathuis ,  Mathias Drton ,  Steffen Lauritzen ,  Martin Wainwright
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   1.030kg
ISBN:  

9780367732608

ISBN 10:   0367732602
Pages:   536
Publication Date:   18 December 2020
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Paperback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Part I: Conditional independencies and Markov properties. 1. Conditional Independence and Basic Markov Properties - Milan Studený 2. Markov Properties for Mixed Graphical Models - Robin Evans 3. Algebraic Aspects of Conditional Independence and Graphical Models - Thomas Kahle, Johannes Rauh, and Seth Sullivant Part II: Computing with factorizing distributions 4. Algorithms and Data Structures for Exact Computation of Marginals - Jeffrey A. Bilmes 5. Approximate Methods for Calculating Marginals and Likelihoods - Nicholas Ruozzi 6. MAP Estimation: Linear Programming Relaxation and Message-Passing Algorithms - Ofer Meshi and Alexander G. Schwing 7. Sequential Monte Carlo Methods - Arnaud Doucet and Anthony Lee Part III: Statistical inference 8. Discrete Graphical Models and their Parametrization - Luca La Rocca and Alberto Roverato 9. Gaussian Graphical Models - Caroline Uhler 10. Bayesian Inference in Graphical Gaussian Models - Hélène Massam 11. Latent Tree Models - Piotr Zwiernik 12.Neighborhood Selection Methods - Po-Ling Loh 12. Nonparametric Graphical Models - Han Liu and John Lafferty 14. Inference in High-Dimensional Graphical Models - Jana Janková and Sara van de Geer Part IV: Causal inference 15. Causal Concepts and Graphical Models - Vanessa Didelez 16. Identication In Graphical Causal Models - Ilya Shpitser 17. Mediation Analysis - Johan Steen and Stijn Vansteelandt 18. Search for Causal Models - Peter Spirtes and Kun Zhang Part V: Applications 19. Graphical Models for Forensic Analysis - A. Philip Dawid and Julia Mortera 20. Graphical Models in Molecular Systems Biology - Sach Mukherjee and Chris Oates 21. Graphical Models in Genetics, Genomics, and Metagenomics - Hongzhe Li and Jing Ma

Reviews

The Handbook of Graphical Models is an edited collection of chapters written by leading researchers and covering a wide range of topics on probabilistic graphical models. The editors, Marloes Maathuis, Mathias Drton, Steffen Lauritzen, and Martin Wainwright, are well-known statisticians and have conducted foundational research on graphical models. They have done a great job of soliciting and organizing chapters authored by top researchers from a variety of disciplines beyond just mathematics, probability and statistics; many authors hail from computer science, electrical engineering, economics, and even philosophy. It is precisely the multidisciplinary nature of this book that makes it stand out from other texts on graphical models. Because of this, the Handbook of Graphical Models will have broad appeal across many disciplines, providing a unique resource and excellent reference for those researching, studying, and using graphical models...Overall, the Handbook of Graphical Models is an important reference on probabilistic graphical models that will be used by researchers in statistics and probability, computer science, electrical engineering and beyond. The book stands out for its broad, multidisciplinary nature, with wide-ranging and largely theoretical coverage of core topics and the latest research on graphical models. - Genevera I. Allen, JASA, August 2020

"""The Handbook of Graphical Models is an edited collection of chapters written by leading researchers and covering a wide range of topics on probabilistic graphical models. The editors, Marloes Maathuis, Mathias Drton, Steffen Lauritzen, and Martin Wainwright, are well-known statisticians and have conducted foundational research on graphical models. They have done a great job of soliciting and organizing chapters authored by top researchers from a variety of disciplines beyond just mathematics, probability and statistics; many authors hail from computer science, electrical engineering, economics, and even philosophy. It is precisely the multidisciplinary nature of this book that makes it stand out from other texts on graphical models. Because of this, the Handbook of Graphical Models will have broad appeal across many disciplines, providing a unique resource and excellent reference for those researching, studying, and using graphical models...Overall, the Handbook of Graphical Models is an important reference on probabilistic graphical models that will be used by researchers in statistics and probability, computer science, electrical engineering and beyond. The book stands out for its broad, multidisciplinary nature, with wide-ranging and largely theoretical coverage of core topics and the latest research on graphical models."" - Genevera I. Allen, JASA, August 2020"

""The Handbook of Graphical Models is an edited collection of chapters written by leading researchers and covering a wide range of topics on probabilistic graphical models. The editors, Marloes Maathuis, Mathias Drton, Steffen Lauritzen, and Martin Wainwright, are well-known statisticians and have conducted foundational research on graphical models. They have done a great job of soliciting and organizing chapters authored by top researchers from a variety of disciplines beyond just mathematics, probability and statistics; many authors hail from computer science, electrical engineering, economics, and even philosophy. It is precisely the multidisciplinary nature of this book that makes it stand out from other texts on graphical models. Because of this, the Handbook of Graphical Models will have broad appeal across many disciplines, providing a unique resource and excellent reference for those researching, studying, and using graphical models...Overall, the Handbook of Graphical Models is an important reference on probabilistic graphical models that will be used by researchers in statistics and probability, computer science, electrical engineering and beyond. The book stands out for its broad, multidisciplinary nature, with wide-ranging and largely theoretical coverage of core topics and the latest research on graphical models."" - Genevera I. Allen, JASA, August 2020

Author Information

Marloes Maathuis is Professor of Statistics at ETH Zurich. Mathias Drton is Professor of Statistics at the University of Copenhagen and the University of Washington. Steffen Lauritzen is Professor of Statistics at the University of Copenhagen. Martin Wainwright is Chancellor's Professor at the University of Berkeley.

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