Elements of Sequential Monte Carlo

FOUNDATIONS AND TRENDS IN MACHINE LEARNING, pp. 187-306, 2019.

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Abstract:

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 ...More

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