Lecture 35 - Sequential Importance Sampling

Lecture PDF: https://www.dropbox.com/s/dtx2vy9me1a... Sequential Bayesian Inference; Importance sampling for the state space model (SSM); Sequential Importance Sampling, Factorization of the importance density, Variance; The Bootstrap Particle Filter, Resampling; Bayesian Recursion formulas, Filtering and marginal likelihood, The Bootstrap Filter implementing the prediction/update recursions, Kalman filter updates for a LG-SSM, Forward-Filtering Backward-Smoothing relations, Forward-Backward two filter smoother; Online Bayesian parameter estimation, MLE Solution and Fisher’s identity, Expectation-Maximization approach, Gaussian Process SSM.