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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the theory of Markov Chain Monte Carlo (MCMC) sampling, discussing the process of sampling from a target distribution using a Markov chain with a transition matrix. It explains the convergence conditions towards stationarity, the choice of transition matrix, and the evolution of the target distribution. The lecture also delves into the detailed balance condition, ergodicity, irreducibility, and aperiodicity of the Markov chain.