Lectures related to Gaussian Corelation Inequality & Anderson's Thum

Covers the basics of probability theory, random variables, joint probability, and inference.

Introduces key concepts in probability and statistics, such as events, Venn diagrams, and conditional probability.

Geodesic Convexity: Theory and Applications

Explores geodesic convexity in metric spaces and its applications, discussing properties and the stability of inequalities.

Convex Sets: Theory and Applications

Explores convex sets, their properties, and applications in optimization.

Probability and Statistics

Introduces key concepts in probability and statistics, illustrating their application through various examples and emphasizing the importance of mathematical language in understanding the universe.

Variance: Definition, Examples, and Theorems

Covers the definition of variance, examples, theorems, and applications in probability theory.

Conditional Expectation

Covers conditional expectation, Fubini's theorem, and their applications in probability theory.