Lectures related to Free entropy

Provides an in-depth analysis of the Random Field Ising Model, covering model description, free entropy, and mean field algorithm.

Introduces the Random-Subcube Model (RSM) for constraint satisfaction problems, exploring its structure, phase transitions, and variable freezing.

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

Covers the concept of point estimation in statistics, focusing on methods to estimate unknown parameters from a given sample.

Explores Belief Propagation on trees, discussing cavity marginals, message passing algorithms, and the computation of free entropy.

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

Covers the analysis of cluster complexity in random graph coloring.

Explores uncorrelated fluctuations, the ideal gas law, and the Langmuir adsorption isotherm.

Discusses the unified formulation of the generalized linear model and the optimization of loss functions.

Explains message passing in graphical models and the matching problem in graph theory.

Explores mutual information and entropy calculation between random variables.

Explains probability distribution, entropy, and Gibbs free entropy, along with the Weiss model.

Explores the cavity method for the run-fill Ising model and the variational method for approximating the Boltzmann distribution.

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

Explores magnetic phase transitions, ferromagnetism, Bethe lattice, Potts model, and free entropy.

Explores Gibbs's entropy, information theory, and the information content of events in non-equiprobable scenarios.

Explores temperature, pressure, and chemical potential in simple systems, along with reversible processes and powers.

Explores variational methods in statistical physics and the Bethe Parisi Mézard approach.

Explores the derivation of the canonical distribution based on Gibbs's entropy and a maximum entropy principle.

Explores irreversible transformations, entropy change, and the irreversibility of real machines compared to the Carnot cycle.