Advertisement

Monte Carlo Methods

  • Adrian Barbu
  • Song-Chun Zhu
Textbook

Table of contents

  1. Front Matter
    Pages i-xvi
  2. Adrian Barbu, Song-Chun Zhu
    Pages 1-17
  3. Adrian Barbu, Song-Chun Zhu
    Pages 19-48
  4. Adrian Barbu, Song-Chun Zhu
    Pages 49-70
  5. Adrian Barbu, Song-Chun Zhu
    Pages 71-96
  6. Adrian Barbu, Song-Chun Zhu
    Pages 97-121
  7. Adrian Barbu, Song-Chun Zhu
    Pages 123-188
  8. Adrian Barbu, Song-Chun Zhu
    Pages 189-209
  9. Adrian Barbu, Song-Chun Zhu
    Pages 211-280
  10. Adrian Barbu, Song-Chun Zhu
    Pages 281-325
  11. Adrian Barbu, Song-Chun Zhu
    Pages 327-366
  12. Adrian Barbu, Song-Chun Zhu
    Pages 367-420
  13. Back Matter
    Pages 421-422

About this book

Introduction

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.

Keywords

Monte Carlo Methods Sequential Monte Carlo Markov Chain Monte Carlo Metropolis-Hastings Gibbs Sampler Swendsen-Wang Cuts Data Driven Markov Chain Monte Carlo Hamiltonian Monte Carlo Stochastic Gradient Descent Langevin Monte Carlo Energy Landscape Mapping Computer Vision Machine Learning Computer Graphics Artificial Intelligence

Authors and affiliations

  • Adrian Barbu
    • 1
  • Song-Chun Zhu
    • 2
  1. 1.Department of StatisticsFlorida State UniversityTallahasseeUSA
  2. 2.Departments of Statistics and Computer ScienceUniversity of California, Los AngelesLos AngelesUSA

Bibliographic information