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Monte Carlo methods
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 C...
| Autores principales: | , |
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| Lenguaje: | eng |
| Publicado: |
Springer
2020
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| Materias: | |
| Acceso en línea: | https://dx.doi.org/10.1007/978-981-13-2971-5 http://cds.cern.ch/record/2711895 |