Before revision:  To investigate this setting, we propose a method to integrate simulations , a strong form of prior knowledge, into machine learning , a combination which to date has been largely unexplored .
After revision:  To investigate this setting, we propose a method to integrate simulations , a strong form of prior knowledge, into machine learning , which builds a black-box model of the system using a large dataset of input sample features and outputs. We consider a setting which is between these two extremes: some details of the system mechanics are known but not enough for creating simulations that can be used to make high quality predictions. In this context we propose using approximate simulations to build a kernel for use in kernelized machine learning methods, such as support vector machines .