Quantum-chemical insights from deep tensor neural networks

Machine learning is an increasingly popular approach to analyse data and make predictions. Here the authors develop a ‘deep learning’ framework for quantitative predictions and qualitative understanding of quantum-mechanical observables of chemical systems, beyond properties trivially contained in t...

Full description

Bibliographic Details
Main Authors: Kristof T. Schütt, Farhad Arbabzadah, Stefan Chmiela, Klaus R. Müller, Alexandre Tkatchenko
Format: Article
Language:English
Published: Nature Publishing Group 2017-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/ncomms13890