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Quantum Machine Learning

Project description

# QML: A Python Toolkit for Quantum Machine Learning [![Build Status](https://travis-ci.org/qmlcode/qml.svg?branch=master)](https://travis-ci.org/qmlcode/qml) [![doi](https://badge.fury.io/py/qml.svg)](https://badge.fury.io/py/qml) [![doi](https://zenodo.org/badge/89045103.svg)](https://zenodo.org/badge/latestdoi/89045103)

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.

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