In recent years, Bayesian methods have been proposed as a solution to a wide range of issues in quantum state and process tomography. In this talk, we make these methods practical by solving three distinct problems: numerical intractability, a lack of informative prior distributions, and an inability to track time-dependent processes. Our approach allows for practical computation of point and region estimators for quantum states and channels, and allows tracking of time-dependent states.
