Before revision:  Importantly, we show that the resulting model approximates the marginal activation probabilities that can be used for prediction of the spread .
After revision:  We show that tractable inference from the learned model generates a better prediction of marginal probabilities compared to the original model. We develop a systematic procedure for learning a mixture of models which further improves prediction quality of the model .