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. A prior probability, in Bayesian statistical inference, is the probability of an event based on established knowledge, before empirical data is collected

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