Two different stochastic models for earthquake occurrence are discussed. Both models are focusing on the spatio-temporal interactions between earthquakes. The parameters in the models are estimated based on Bayesian updating of priors, using empirical data to derive posterior distributions. The first model is a marked point process model in which each earthquake is represented as a marked point in space and time. The second model is a hierarchical Bayesian space-time model in which the earthquakes are represented by potentials in a grid. The final ambition for the models is to make predictions on the occurrence of earthquakes.