6.438  Algorithms for Inference

Introduction to statistical inference with probabilistic graphical models. Directed and undirected graphical models; factor graphs; Gaussian models. Hidden Markov models, linear dynamical systems. Sum‐product and junction tree algorithm. Forward‐backward algorithm; Kalman filtering and smoothing. Variational methods, mean‐field theory, and loopy belief propagation. Particle methods and filtering. Min‐sum algorithm; Viterbi algorithm. Building graphical models from data; parameter estimation, learning structure. Selected special topics.