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Monte Carlo Methods

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Monte Carlo Methods/ by Adrian Barbu, Song-Chun Zhu.
Author:	Barbu, Adrian.
other author:	Zhu, Song-Chun.
Description:	XVI, 422 p. 250 illus., 185 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Computer mathematics. -
Online resource:	https://doi.org/10.1007/978-981-13-2971-5
ISBN:	9789811329715

Monte Carlo Methods
Barbu, Adrian.

Monte Carlo Methods[electronic resource] /by Adrian Barbu, Song-Chun Zhu. - 1st ed. 2020. - XVI, 422 p. 250 illus., 185 illus. in color.online resource.

1 Introduction to Monte Carlo Methods -- 2 Sequential Monte Carlo -- 3 Markov Chain Monte Carlo - the Basics -- 4 Metropolis Methods and Variants -- 5 Gibbs Sampler and its Variants -- 6 Cluster Sampling Methods -- 7 Convergence Analysis of MCMC -- 8 Data Driven Markov Chain Monte Carlo -- 9 Hamiltonian and Langevin Monte Carlo -- 10 Learning with Stochastic Gradient -- 11 Mapping the Energy Landscape.

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.

ISBN: 9789811329715

Standard No.: 10.1007/978-981-13-2971-5doiSubjects--Topical Terms:

1199796
Computer mathematics.

LC Class. No.: QA71-90

Dewey Class. No.: 518

Monte Carlo Methods
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505 0 $a 1 Introduction to Monte Carlo Methods -- 2 Sequential Monte Carlo -- 3 Markov Chain Monte Carlo - the Basics -- 4 Metropolis Methods and Variants -- 5 Gibbs Sampler and its Variants -- 6 Cluster Sampling Methods -- 7 Convergence Analysis of MCMC -- 8 Data Driven Markov Chain Monte Carlo -- 9 Hamiltonian and Langevin Monte Carlo -- 10 Learning with Stochastic Gradient -- 11 Mapping the Energy Landscape.
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