Monte Carlo Methods
Adrian Barbu () and
Song-Chun Zhu ()
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Adrian Barbu: Florida State University, Department of Statistics
Song-Chun Zhu: University of California, Los Angeles, Departments of Statistics and Computer Science
in Springer Books from Springer
Date: 2020
ISBN: 978-981-13-2971-5
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Chapters in this book:
- Ch 1 Introduction to Monte Carlo Methods
- Adrian Barbu and Song-Chun Zhu
- Ch 2 Sequential Monte Carlo
- Adrian Barbu and Song-Chun Zhu
- Ch 3 Markov Chain Monte Carlo: The Basics
- Adrian Barbu and Song-Chun Zhu
- Ch 4 Metropolis Methods and Variants
- Adrian Barbu and Song-Chun Zhu
- Ch 5 Gibbs Sampler and Its Variants
- Adrian Barbu and Song-Chun Zhu
- Ch 6 Cluster Sampling Methods
- Adrian Barbu and Song-Chun Zhu
- Ch 7 Convergence Analysis of MCMC
- Adrian Barbu and Song-Chun Zhu
- Ch 8 Data Driven Markov Chain Monte Carlo
- Adrian Barbu and Song-Chun Zhu
- Ch 9 Hamiltonian and Langevin Monte Carlo
- Adrian Barbu and Song-Chun Zhu
- Ch 10 Learning with Stochastic Gradient
- Adrian Barbu and Song-Chun Zhu
- Ch 11 Mapping the Energy Landscape
- Adrian Barbu and Song-Chun Zhu
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprbok:978-981-13-2971-5
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DOI: 10.1007/978-981-13-2971-5
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