AUTOMATICALLY ASCERTAINING AN OPTIMAL ARCHITECTURE FOR A NEURAL NETWORK

A computer-implemented method for ascertaining an optimal architecture for a neural network that solves a given task in accordance with given boundary conditions and/or optimization goals. The method includes: providing a graph of the possible architectures of nodes and edges, wherein nodes correspond to data, edges correspond to parameterized operations to be carried out on the data, and a path which traverses the entire graph corresponds to an architecture; in a search phase, generating candidate architectures based on already known architectures, wherein the candidate architectures are similar but not identical to the known architectures in accordance with a predetermined criterion; evaluating the candidate architectures using the given boundary conditions and/or optimization goals;ascertaining a candidate architecture having the best rating as the sought optimal architecture.