# Elements of Sequential Monte Carlo

@article{Naesseth2019ElementsOS,
title={Elements of Sequential Monte Carlo},
author={C. A. Naesseth and F. Lindsten and Thomas Bo Sch{\"o}n},
journal={ArXiv},
year={2019},
volume={abs/1903.04797}
}
• Published 2019
• Mathematics, Computer Science
• ArXiv
A core problem in statistics and probabilistic machine learning is to compute probability distributions and expectations. This is the fundamental problem of Bayesian statistics and machine learning, which frames all inference as expectations with respect to the posterior distribution. The key challenge is to approximate these intractable expectations. In this tutorial, we review sequential Monte Carlo (SMC), a random-sampling-based class of methods for approximate inference. First, we explain… Expand
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