Lectures related to Subgraphs vs Induced Subgraphs

Minimum Spanning Trees: Prim's Algorithm

Explores Prim's algorithm for minimum spanning trees and introduces the Traveling Salesman Problem.

Graph Algorithms II: Traversal and Paths

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

Graphs: Properties and Representations

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

Graphical Models: Representing Probabilistic Distributions

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

Graph Theory: Connectivity and Properties

Explores the properties of undirected and directed graphs, emphasizing connectivity and network topology modeling.

Graph Algorithms: Modeling and Traversal

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

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.

Connectivity in Graph Theory

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

Fixed Points in Graph Theory

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

Minimal Spanning Tree

Covers the concept of weighted graphs and the Greedy algorithm for finding a minimal spanning tree.

Shortest Path Algorithms: BFS and Dijkstra

Explores Breadth-First Search and Dijkstra's algorithm for finding shortest paths in graphs.

Belief Propagation

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

Handling Networks: Graph Theory

Covers the fundamentals of handling networks and centrality measures in graph theory.

Networked Control Systems: Coordination Among Agents

Explores coordination among agents in networked control systems through graph theory and real-world examples.

Networked Control Systems: Convergence Rate and Digraphs

Explores convergence rate in networked control systems and consensus in digraphs, emphasizing the challenges of computing Pess(A) and weight assignment.

Handling Networks: Graph Theory

Explores graph theory concepts, centrality measures, and real-world network properties, providing insights into handling diverse types of networks.

Probabilistic method and its applications

Introduces the probabilistic method to prove existence results in graph theory.

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.

Convergence of Random Walks Log in to Mediaspace to watch this video

Explores the convergence of random walks on graphs and the properties of weighted adjacency matrices.

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.