Concept

Graph coloring

Related lectures (32)

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Explores advanced graph coloring concepts, including planted coloring, rigidity threshold, and frozen variables in BP fixed points.

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

Explores graph algorithms like BFS and DFS, discussing shortest paths, spanning trees, and data structures' role.

Explores the statistical physics of clusters, focusing on complexity and equilibrium behavior.

Compares random and symmetrical graph coloring in terms of cluster colorability and equilibrium.

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

Explores properties of clusters and colorability threshold in graph coloring, including average connectivity and rigidity.

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

Introduces the basics of graph algorithms, covering traversal, representation, and data structures for BFS and DFS.

Explores memory management, graph representation, and traversal algorithms in Python, emphasizing BFS and DFS.

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

Explores Markov chains, focusing on the coloring problem and algorithm analysis.

Covers the basics of graph algorithms, focusing on modeling and representation of graphs in memory.

Covers the independence polynomial of a dependency graph and related concepts such as graph coloring and directed graph properties.

Covers the basics of information theory, entropy, and fixed points in graph colorings and the Ising model.

Introduces graph theory basics, Ramsey theory, and graph coloring concepts.

Explores Belief Propagation for graph coloring and its convergence properties.

Covers register allocation techniques and strategies, including graph coloring and spilling integration.

Explains entropy and free energy computation in graph coloring.