1. A method of selecting a batch of input data from available input data for parallel evaluation by a function, the method comprising: via a controller, modeling the function as drawn from a Gaussian process; using observations to determine a mean and a variance of the modeled function; determining an upper confidence bound from the determined mean and variance; via the controller, applying a decision rule to select input data from the available input data to add to the batch of input data, wherein the selection is based on a domain-specific time varying parameter; hallucinating intermediate observations within the batch; via the controller, using the hallucinated observations with the decision rule to select subsequent input data from the available input data for the batch of input data via the controller; via the controller, evaluating the input data of the batch in parallel with the function; and storing the resulting determined data outputs in a memory device.