Monte Carlo Methods PDF
By:Adrian Barbu,Song-Chun Zhu
Published on 2020-02-24 by Springer Nature
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.
This Book was ranked at 26 by Google Books for keyword computer vision medical robotics.
Book ID of Monte Carlo Methods's Books is 8aDSDwAAQBAJ, Book which was written byAdrian Barbu,Song-Chun Zhuhave ETAG "5aewQuSmGXc"
Book which was published by Springer Nature since 2020-02-24 have ISBNs, ISBN 13 Code is 9789811329715 and ISBN 10 Code is 9811329710
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Book which have "422 Pages" is Printed at BOOK under CategoryMathematics
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