Neural Networks

A Python-interfaced neural network model for the rapid prediction of QTAIM atomic charges of C, H, O and N atoms in gas-phase organic and biological molecules.

A deep learning code based on the SchNet architecture for training models on atomic (1-body) and pairwise (2-body) QTAIM properties. Supports CPU and GPU execution.

A graphical user interface for the prediction and visualisation of QTAIM atomic properties using feed-forward neural network models. Includes the built-in NNAIMQ model for Bader charges.