Learning Latent Models in Graphical Structures

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Related lectures (29)

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Dependence Concepts and Copulas

Explores dependence concepts, copulas, correlation fallacies, and rank correlations in statistics.

Introduction to Continuous Random Variables: Probability Distributions

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Basics of Risk Analysis and Management

Introduces the basics of risk analysis and management in civil engineering, covering distributions, statistical reminders, and mathematical interpretation techniques.

Continuous Random Variables

Explores continuous random variables, density functions, joint variables, independence, and conditional densities.

Propagation of Uncertainty: Estimation and Distribution

Discusses estimation and propagation of uncertainty in random variables and the importance of managing uncertainty in statistical analysis.

Continuous Random Variables: Distributions and Examples

Explores continuous random variables, density functions, and distribution laws with practical examples.

Elements of Statistics: Probability, Distributions, and Estimation

Covers probability theory, distributions, and estimation in statistics, emphasizing accuracy, precision, and resolution of measurements.

Supervised Learning Fundamentals

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.

Probability Distributions

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

Quantifying Statistical Dependence

Delves into quantifying statistical dependence through covariance, correlation, and mutual information.