Quantum Monte Carlo: Basic Concepts

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Explores Markov chains and their applications in algorithms, focusing on user impatience and faithful sample generation.

Markov Chains: Simulation and Optimization

Explores Markov chains, Metropolis-Hastings, and simulation for optimization purposes, highlighting the significance of ergodicity in efficient variable simulation.

Optimization and Simulation

Covers optimization and simulation techniques for drawing from multivariate distributions and dealing with correlations.

Stochastic Simulation: Markov Chains and Monte Carlo

Covers Markov chains, Monte Carlo methods, low discrepancy sequences, and multidimensional integrals computation.

Biased Monte Carlo Markov Chain

Explores Biased Monte Carlo Markov Chain, including Bayes-optimal estimation and Metropolis-Hastings algorithm.

Monte Carlo Moves in Simulation

Explores Monte Carlo moves in simulation, including trial moves and biased moves, comparing Monte Carlo with Molecular Dynamics.

Kohonen Maps: Mini Projects 1

Covers the implementation of Kohonen Maps in mini project 1.

Markov chains

Covers Markov chains, Monte Carlo sampling, isotropy, and the curse of dimensionality.

Markov Chains and Algorithm Applications

Covers Markov chains and their applications in algorithms, focusing on Markov Chain Monte Carlo sampling and the Metropolis-Hastings algorithm.

Probability & Stochastic Processes

Covers applied probability, stochastic processes, Markov chains, rejection sampling, and Bayesian inference methods.