Applied Probability & Stochastic Processes

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Related lectures (32)

Spectral Gap in Markov Chains

Explores the spectral gap in Markov chains and its impact on convergence speed.

Markov Chains: Ergodicity and Stationary Distribution

Explores ergodicity and stationary distribution in Markov chains, emphasizing convergence properties and unique distributions.

Markov Chains: Properties and Expectations

Explores Markov chains' properties, expectations, and recurrence in Poisson processes.

Stochastic Models for Communications: Discrete-Time Markov Chains - First Passage Time

Explores discrete-time Markov chains, emphasizing first passage time probabilities and minimal solutions.

Discrete-Time Markov Chains: Reversible Chains

Covers reversible discrete-time Markov chains in communication models.

Stochastic Models: Absorbing Markov Chains Examples

Covers examples of absorbing Markov chains in discrete time.

Markov Chains: Transition Probabilities

Explores Markov chains, transition matrices, distribution, and random walks.

Recurrence and transience in markov chains

Explores the concepts of recurrence and transience in continuous time Markov chains.

Markov Chains: Communicating Classes

Explores communicating classes in Markov chains, distinguishing between transient and recurrent classes, and delves into the properties of these classes.

Birth & Death Chains: Analysis & Probabilities

Explores birth and death chains, hitting probabilities, and expected game durations in Markov chains.

Pseudorandomness: Theory and Applications

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

NISQ and IBM Q

Explores NISQ devices and IBM Q, covering noisy quantum circuits, qubit technologies, and quantum algorithm development.

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