Skip to main content

Quantum Machine Learning

Project description

# QML: A Python Toolkit for Quantum Machine Learning [![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:

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”

## 2) Get help:

Documentation and installation instruction is found at:

## 3) License:

QML is freely available under the terms of the MIT license.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for qml, version
Filename, size File type Python version Upload date Hashes
Filename, size qml- (41.0 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page