1. Each category is assigned a prior probability (301).

2. A Gaussian process can be used as a prior probability distribution over functions in Bayesian inference.

3. The convergence and stability of the expansion are ensured by a prior probability measure on the expansion coefficients.

4. In the Bayesian approach, the data are supplemented with additional information in the form of a prior probability distribution.

5. In algorithmic information theory, algorithmic probability, also known as Solomonoff probability, is a mathematical method of assigning a prior probability to a given observation.