Bayes-optimal inference for spreading processes on random networks.

We consider a class of spreading processes on networks, which generalize commonly used epidemic models such as the SIR model or the SIS model with a bounded number of reinfections. We analyze the related problem of inference of the dynamics based on its partial observations. We analyze these inference problems on random networks via a message-passing inference algorithm derived from the belief propagation (BP) equations.