Statistical Physics of Clusters

Related lectures (29)

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

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.

Covers the analysis of cluster complexity in random graph coloring.

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

Covers the computation of Bethe free entropy and the interpretation of messages between variables and factors.

Covers the Curie-Weiss model in Statistical Physics, including magnetization probability, free entropy, and the cavity method.

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

Covers entropy, its definition, and its implications in thermodynamics.

Covers the K-means algorithm for clustering data samples into k classes without labels, aiming to minimize the loss function.