Belief Propagation on Trees

This lecture introduces Belief Propagation (BP) on trees, focusing on solving problems with variable interactions. The instructor explains the concept of cavity marginals and message passing algorithms, illustrating how to compute true marginals and free entropy. The lecture covers the application of BP to Ising models on trees, discussing phase transitions and the convergence of marginals. The instructor also explores the computation of free energy and the efficiency of BP in solving problems on tree topologies.