Random Walk and Diffusion

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Related lectures (30)

Page 3 of 3

Explores binomial and Poisson mass functions, calculating probabilities and discussing distribution functions of random variables.

Probability and Statistics

Covers fundamental concepts in probability and statistics, including distributions, properties, and expectations of random variables.

Stochastic Processes: Symmetric Random Walk

Covers the properties of the symmetric random walk in stochastic processes.

Elementary Distributions Factsheet

Covers elementary distributions like Bernoulli, Binomial, Geometric, Negative Binomial, Poisson, and Multinomial.

Probability Theory: Discrete Random Variables

Covers discrete random variables, probability mass function, properties, and binomial distribution with illustrative examples.

Probability and Statistics

Introduces probability, statistics, distributions, inference, likelihood, and combinatorics for studying random events and network modeling.

Advanced Probability

Delves into advanced probability theory, covering inequalities, trials, distributions, and calculations for probabilities and expectations.

Fundamental Limits of Gradient-Based Learning

Delves into the fundamental limits of gradient-based learning on neural networks, covering topics such as binomial theorem, exponential series, and moment-generating functions.

Statistical Models: Families and Transformations

Explores statistical models, families of distributions, transformations, and their applications in probability theory.

Probability Distributions

Covers various probability distributions and their applications in real-world scenarios.