  Using a new Bayesian method for solving inverse quantum problems, potentials
of quantum systems are reconstructed from coordinate measurements in
non-stationary states. The approach is based on two basic inputs: 1. a
likelihood model, providing the probabilistic description of the measurement
process as given by the axioms of quantum mechanics, and 2. additional "a
priori" information implemented in form of stochastic processes over
potentials.
