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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 concept of Monte Carlo Markov Chains, focusing on iterative algorithms for sampling trial configurations and accepting states based on probabilities. It also discusses Metropolis-Hastings and Gibbs sampling methods, emphasizing detailed balance and convergence criteria.