Lecture

Monte Carlo Markov Chains

Description

This lecture covers the theory of Markov chains and Monte Carlo methods, focusing on the Metropolis-Hastings algorithm. It explains the concept of equilibrium distribution, transition matrices, and the process of sampling using trial configurations.

Instructor

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Official source

https://mediaspace.epfl.ch/media/0_6r2owwbt

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Ontological neighbourhood

Statistics

Statistical inference: Bayesian inference

Data collection: Statistical sampling

Mathematics

Probability theory: Topics in probability theory

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