Markov Chains: Applications and Sampling Methods

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Description

This lecture covers the basics of Markov chains, including the main concepts like state distribution, ergodic chains, and importance sampling. It also delves into algorithmic applications and sampling methods such as Monte Carlo and rejection sampling.

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Ontological neighbourhood

Mathematics

Discrete mathematics: Graph theory

Related lectures (32)

https://mediaspace.epfl.ch/media/0_6psouyc0

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In course

DEMO: ullamco labore

Ontological neighbourhood

Mathematics

Discrete mathematics: Graph theory

Related lectures (32)

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