Lecture

Markov Chains and Applications

In course

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Description

This lecture covers the fundamentals of Markov chains, including the Ising Model, Metropolis algorithm, and Glauber dynamics. It explores heat bath dynamics, binary alphabet, spins, and degrees of freedom. The lecture delves into the application of Markov chains in various scenarios, such as the Ising Model and Medropolis algorithm.

Instructors (2)

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Official source

https://mediaspace.epfl.ch/media/0_ji8czr5k

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Ontological neighbourhood

Physics

Condensed matter physics: Phase transitions

Mathematics

Discrete mathematics: Graph theory

Statistics

Statistical inference: Bayesian inference

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