03923nam 22007095 450 991048383160332120250505001825.0981-13-2971-010.1007/978-981-13-2971-5(CKB)4100000010480199(DE-He213)978-981-13-2971-5(MiAaPQ)EBC6122025(PPN)24297760X(EXLCZ)99410000001048019920200224d2020 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierMonte Carlo Methods /by Adrian Barbu, Song-Chun Zhu1st ed. 2020.Singapore :Springer Nature Singapore :Imprint: Springer,2020.1 online resource (XVI, 422 p. 250 illus., 185 illus. in color.) 981-13-2970-2 Includes bibliographical references and index.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.MathematicsData processingComputer scienceMathematicsMathematical statisticsImage processingDigital techniquesComputer visionStatisticsStatisticsComputational Mathematics and Numerical AnalysisProbability and Statistics in Computer ScienceComputer Imaging, Vision, Pattern Recognition and GraphicsStatistical Theory and MethodsStatistics in Engineering, Physics, Computer Science, Chemistry and Earth SciencesMathematicsData processing.Computer scienceMathematics.Mathematical statistics.Image processingDigital techniques.Computer vision.Statistics.Statistics.Computational Mathematics and Numerical Analysis.Probability and Statistics in Computer Science.Computer Imaging, Vision, Pattern Recognition and Graphics.Statistical Theory and Methods.Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.519.282Barbu Adrianauthttp://id.loc.gov/vocabulary/relators/aut1002774Zhu Song-Chunauthttp://id.loc.gov/vocabulary/relators/autMiAaPQMiAaPQMiAaPQBOOK9910483831603321Monte Carlo Methods2301695UNINA