Abstract: A method for determining an optimal architecture of a neural network. The method includes: defining a search space by means of a context-free grammar; training neural networks with candidate architectures on the training data, and validating the trained neural networks on the validation data; initializing a Gaussian process, wherein the Gaussian process comprises a Weisfeiler-Lehman graph kernel; adapting the Gaussian process such that given the candidate architectures, the Gaussian process predicts the validation achieved with these candidate architectures; and performing a Bayesian optimization for finding the candidate architecture that achieved the best performance.