QML: A Python Toolkit for Quantum Machine Learning
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|Build Status| |doi| |doi|

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:
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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.

.. |Build Status| image:: https://travis-ci.org/qmlcode/qml.svg?branch=master
   :target: https://travis-ci.org/qmlcode/qml
.. |doi| image:: https://badge.fury.io/py/qml.svg
   :target: https://badge.fury.io/py/qml
.. |doi| image:: https://zenodo.org/badge/89045103.svg
   :target: https://zenodo.org/badge/latestdoi/89045103
