Lectures related to Renormalization: AQFT

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.

Automorphism groups of trees and graphs

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

Graph Algorithms: Modeling and Traversal

Covers graph algorithms, modeling relationships between objects, and traversal techniques like BFS and DFS.

Graph Algorithms II: Traversal and Paths

Explores graph traversal methods, spanning trees, and shortest paths using BFS and DFS.

Fixed Points in Graph Theory

Focuses on fixed points in graph theory and their implications in algorithms and analysis.

Handling Network Data

Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.

Automorphism groups: Trees and Graphs

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

Graph Theory Fundamentals

Covers the fundamentals of graph theory, including vertices, edges, degrees, walks, connected graphs, cycles, and trees, with a focus on the number of edges in a tree.

Belief Propagation

Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.

Stein Algorithm: Polynomial Identity Testing

Explores the Stein algorithm for polynomial identity testing and the minimization of a cut problem.

Automorphism Groups: Trees and Graphs III

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

Quantum Field Theory: Renormalization

Covers the concept of renormalization in quantum field theory, focusing on regularization and divergences removal.

Connectivity in Graph Theory

Covers the fundamentals of connectivity in graph theory, including paths, cycles, and spanning trees.

Real Functions: Graphs and Properties

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

Quantum Field Theory: Loop Corrections and Counter Terms Log in to Mediaspace to watch this video

Explores loop corrections and counter terms in quantum field theory, showcasing how divergences are handled and predictions are extracted from loop calculations.

Graphs and Networks: Basics and Applications Log in to Mediaspace to watch this video

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

Statistical Analysis of Network Data Log in to Mediaspace to watch this video

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

Graphs in Deep Learning: Applications and Techniques Log in to Mediaspace to watch this video

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

Graph Theory and Network Flows Log in to Mediaspace to watch this video

Introduces graph theory, network flows, and flow conservation laws with practical examples and theorems.