Lecture

Markov Chains and Algo Applications

In course

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Description

This lecture covers Markov chains, Metropolis algorithm, Glauber dynamics, heat bath dynamics, simulation results, and their applications in algorithms. It discusses detailed balance, Gibbs sampling, and general measures in the context of Markov chains.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_majbm4tn

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Ontological neighbourhood

Statistics

Statistical inference: Bayesian inference

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