Lectures related to Petersen graph

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

Automorphism groups of trees and graphs II

Explores the uniqueness of trees, automorphism groups, Cayley-Abels graphs, and constructing vertex-transitive subgroups with prescribed local actions.

Automorphism Groups: Trees and Graphs III

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

Statistical Analysis of Network Data

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

Graphical Models: Representing Probabilistic Distributions

Covers graphical models for probabilistic distributions using graphs, nodes, and edges.

Graphs: Properties and Representations

Covers graph properties, representations, and traversal algorithms using BFS and DFS.

Renormalization: AQFT

Covers the concept of renormalization in Algebraic Quantum Field Theory.

Real Functions: Graphs and Properties

Explores real functions, their graphs, properties, and transformations, including symmetry and surjection.

Linear Algebra: Matrix Representation

Explores linear applications in R² and matrix representation, including basis, operations, and geometric interpretation of transformations.

Vector Algebra: Scalar Product

Explores the scalar product of vectors, including properties and calculation methods.

Linear Transformations: Matrices and Kernels

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Understanding Surface Integrals

Explores surface integrals, emphasizing physical interpretation and mathematical calculations in vector fields and domains.

Automorphism groups of trees and graphs

Explores automorphisms of graphs, focusing on automorphism groups, Cayley-Abels graphs, and quasi-isometry.

Geometry of the Triangle

Covers the geometry of the triangle, including inequalities, heights, and centers.

Graphical models: Inference and Factor Graphs

Explores graphical models, factor graphs, and probabilistic inferences in complex systems.

Graphs in Deep Learning: Applications and Techniques

Explores the role of graphs in deep learning, focusing on their structure, applications, and techniques for processing graph data.

Anomalous Topological Networks: Theory and Experiment

Explores anomalous robustness in nonreciprocal topological networks, covering topological Floquet states, unitary scattering networks, and practical implementations.

Pseudorandomness: Theory and Applications

Explores pseudorandomness theory, AI challenges, pseudo-random graphs, random walks, and matrix properties.

Iterated Integrals: Order and Domains

Explores iterated integrals, order, domains, and symmetrical roles of variables in 2D space.

Eigenvalues and Sequences

Discusses finding d-regular graphs with specific eigenvalue properties and the existence of Ramasugan sequences for d-opt prime numbers.