QML: A Python Toolkit for Quantum Machine Learning
QML is a Python2/3-compatible toolkit for representation learning of properties of molecules and solids.
Current list of contributors:
- Anders S. Christensen (University of Basel)
- Felix A. Faber (University of Basel)
- Bing Huang (University of Basel)
- Lars A. Bratholm (University of Copenhagen)
- Alexandre Tkatchenko (University of Luxembourg)
- Klaus-Robert Müller (Technische Universität Berlin/Korea University)
- O. Anatole von Lilienfeld (University of Basel)
1) Citing QML:
Until the preprint is available from arXiv, please cite this GitHub repository as:
AS Christensen, LA Bratholm, FA Faber, B Huang, A Tkatchenko, KR Müller, OA von Lilienfeld (2017) "QML: A Python Toolkit for Quantum Machine Learning" https://github.com/qmlcode/qml
2) Get help:
Documentation and installation instruction is found at: http://www.qmlcode.org/
3) License:
QML is freely available under the terms of the MIT license.