Stochastic models, diffusion models in particular, are widely used in science, engineering and economics.Inferring the parameter values from data is often complicated by the fact that the underlying stochastic processes are only partially observed, Examples include inference of discretely observed diffusion processes, stochastic volatility models, and double stochastic Poisson (Cox) processes.Likelihood based inference faces the difficulty that the likelihood is usually not available even numerically.