1. A method for determining a sparse Gaussian process model, which is performed in a hardware-based model calculation unit, the method comprising: providing supporting point data points, a parameter vector based thereon, and corresponding hyperparameters; determining or providing virtual supporting point data points for the sparse Gaussian process model; and determining a parameter vector Q y * for the sparse Gaussian process model with the aid of a Cholesky decomposition of a covariant matrix K M between the virtual supporting point data points and as a function of the supporting point data points, the parameter vector based thereon, and the corresponding hyperparameters, which define the sparse Gaussian process model.