Elements of Sequential Monte Carlo

Understand

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.