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Monte Carlo Methods
~
Barbu, Adrian.
Monte Carlo Methods
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Monte Carlo Methods/ by Adrian Barbu, Song-Chun Zhu.
作者:
Barbu, Adrian.
其他作者:
Zhu, Song-Chun.
面頁冊數:
XVI, 422 p. 250 illus., 185 illus. in color.online resource. :
Contained By:
Springer Nature eBook
標題:
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. -
電子資源:
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:
782247
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
LC Class. No.: QA71-90
Dewey Class. No.: 518
Monte Carlo Methods
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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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