General Explosions

Related lectures (31)

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Covers Markov chains, Metropolis algorithm, Glauber dynamics, and heat bath dynamics.

Explores Markov chains, focusing on the coloring problem and algorithm analysis.

Explores first passage times, strong Markov property, and state recurrence/transience in Markov chains.

Covers stochastic models for communications, focusing on random variables, Markov chains, Poisson processes, and probability calculations.

Explores Markov chains, Ising Model, Metropolis algorithm, and Glauber dynamics.

Covers the basics of Markov chains and their algorithmic applications.

Explores Markov chains with absorbing classes through exercises on transition matrices and expected values.

Covers the definitions and state probabilities of discrete-time Markov chains.

Covers the simplex algorithm, pivoting, elementary row operations, and transformations to find matrix Q.

Covers the theory and applications of Markov chains, focusing on key concepts and properties.