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Related lectures (29)

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Explores different types of convergence of random variables and their properties, including quadratic mean and convergence in probability.

Covers basic probability theory, conditional probability, independence, and Bayes' Theorem.

Explores random variables, their variability, realization of random processes, and the scientific method in material science.

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Covers the concept of convergence in distribution for random variables and its significance in probability theory.

Introduces the basics of probability theory, covering events, intersections, unions, and sample space.

Explores the motivation and ideas behind convolutional networks, emphasizing weight sharing and pooling layers.

Explores Pierre-Simon Laplace's classical theory of probability through examples like dice rolls and lotteries.

Explores the Curie-Weiss model, illustrating how temperature affects magnetization in materials.