Explores handling network data, including types of graphs, real-world network properties, and node importance measurement.
Distinguishes between subgraphs and induced subgraphs in graph theory, illustrating the construction of minimal spanning trees.
Explores Belief Propagation in graphical models, factor graphs, spin glass examples, Boltzmann distributions, and graph coloring properties.
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.
Covers the concept of networks, graphs, subgraphs, directed graphs, and indegree in network theory.
