Structure Seer – a machine learning model for chemical structure elucidation from node labelling of a molecular graph

Abstract

We introduce a graph convolution based machine-learning model which provides a quantitative probabilistic prediction on the atom connectivity based on the composition of the molecule along with a list of atom-attributed isotropic shielding constants.