bayesian inference

Bayesian inference requires an intractable normalizing constant, and MCMC works around it. The signal is explaining the acceptance ratio, detailed balance, and why you can drop the constant entirely. Here is the answer.

The Kalman filter is optimal Bayesian tracking under linear-Gaussian assumptions, and it amounts to two steps repeated forever. The signal is explaining what the gain trades off and when the assumptions break. Here is the answer.