Lectures related to Information Measures

Explores random walks, Moran model, bacterial chemotaxis, entropy, information theory, and coevolving sites in proteins.

Covers linear transformations using matrices, focusing on linearity, image, and kernel.

Explores orthogonality, dot product properties, vector norms, and angle definitions in vector spaces.

Covers the basics of information theory and its applications in various fields.

Covers information measures like entropy, joint entropy, and mutual information in information theory and data processing.

Explores weak derivatives in Sobolev spaces, discussing their properties and uniqueness.

Explores orthogonal matrices and transformations, emphasizing preservation of norms and angles.

Covers the goals and motivations of representation theory, focusing on associative algebras and homomorphisms.