.. Amp documentation master file, created by sphinx-quickstart on Thu Jul 30 17:27:50 2015. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Amp: Atomistic Machine-learning Package ======================================= `Amp `_ is an open-source package designed to easily bring machine-learning to atomistic calculations. This project is being developed at Brown University in the School of Engineering, primarily by **Andrew Peterson** and **Alireza Khorshidi**, and is released under the GNU General Public License. Please see the project's `git repository `_ for the latest version, news, or a place to report an issue. You can read about Amp in the below paper; if you find Amp useful, we would appreciate if you cite this work: Khorshidi & Peterson, "Amp: A modular approach to machine learning in atomistic simulations", *Computer Physics Communications* 207:310-324, 2016. |amp_paper| .. |amp_paper| raw:: html DOI:10.1016/j.cpc.2016.05.010 **Manual**: .. toctree:: :maxdepth: 1 introduction.rst theory.rst credits.rst releasenotes.rst installation.rst useamp.rst examplescripts.rst analysis.rst neuralnetwork.rst building.rst moredescriptor.rst moremodel.rst tensorflow.rst databases.rst develop.rst **Module autodocumentation**: .. toctree:: :maxdepth: 1 modules/main.rst modules/descriptor.rst modules/model.rst modules/regression.rst modules/utilities.rst modules/analysis.rst **Indices and tables** * :ref:`genindex` * :ref:`modindex` * :ref:`search`