Language: English
Published by Springer Nature Singapore, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
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Language: English
Published by Springer Nature Singapore, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Language: English
Published by Springer Verlag, Singapore, SG, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
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Hardback. Condition: New. 2020 ed.
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Gebunden. Condition: New. A Monte Carlo textbook suitable for students and researchers in the areas of computer vision, machine learning, robotics, artificial intelligence, graphics, etcAn easy to understand textbook featuring a wealth of sample applications.
Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.
Language: English
Published by Springer Verlag, Singapore, SG, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. 2020 ed.
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Language: English
Published by Springer, Springer Feb 2020, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research. 440 pp. Englisch.
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Buch. Condition: Neu. Monte Carlo Methods | Adrian Barbu (u. a.) | Buch | xvi | Englisch | 2020 | Springer | EAN 9789811329708 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.
Language: English
Published by Springer, Springer Feb 2020, 2020
ISBN 10: 9811329702 ISBN 13: 9789811329708
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Buch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book seeks to bridge the gap between statistics and computer science. It provides an overview of Monte Carlo methods, including Sequential Monte Carlo, Markov Chain Monte Carlo, Metropolis-Hastings, Gibbs Sampler, Cluster Sampling, Data Driven MCMC, Stochastic Gradient descent, Langevin Monte Carlo, Hamiltonian Monte Carlo, and energy landscape mapping. Due to its comprehensive nature, the book is suitable for developing and teaching graduate courses on Monte Carlo methods. To facilitate learning, each chapter includes several representative application examples from various fields. The book pursues two main goals: (1) It introduces researchers to applying Monte Carlo methods to broader problems in areas such as Computer Vision, Computer Graphics, Machine Learning, Robotics, Artificial Intelligence, etc.; and (2) it makes it easier for scientists and engineers working in these areas to employ Monte Carlo methods to enhance their research.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 440 pp. Englisch.