bayesian inference

Bayesian inference needs an intractable normalizing constant, and MCMC sidesteps it. The signal is explaining the acceptance ratio, detailed balance, and why you can skip the constant entirely. Here is the answer.

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