Lectures related to Pseudo Randomness in Graphs

Introduces the basics of graphs and networks, covering definitions, paths, trees, flows, circulation, and spanning trees.

Explores automorphism groups in trees and graphs, focusing on ends and types of automorphisms.

Introduces network data structures, models, and analysis techniques, emphasizing permutation invariance and Erdős-Rényi networks.

Explores interlacing polynomials, real rooted theorems, and pseudo-probabilistic methods in polynomial analysis.

Explores isogenic graphs, spectral properties, and mathematical applications in modular forms and cryptography.

Explores automorphism groups of trees and graphs, including actions on trees and group homomorphisms.

Covers graphical models for probability distributions and factor graphs representation.

Covers differentiable functions, extreme points, and the Lagrange multiplier method for optimization.