software . 2017

Amp: The Atomistic Machine-Learning Package V0.6

Khorshidi, Alireza; Ulissi, Zachary; El Khatib, Muammar; Peterson*, Andrew;
Open Access
  • Published: 31 Jul 2017
  • Publisher: Zenodo
Abstract
<p>*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.  *Amp* allows for the modular representation of the potential energy surface, enabling the user to specify or create descriptor and regression methods.</p> <p>This project lives at:<br> https://bitbucket.org/andrewpeterson/amp</p> <p>Documentation lives at:<br> http://amp.readthedocs.org</p> <p>Users' mailing list lives at:<br> https://listserv.brown.edu/?A0=AMP-USERS</p> <p>...
Subjects
ACM Computing Classification System: GeneralLiterature_REFERENCE(e.g.,dictionaries,encyclopedias,glossaries)
free text keywords: Genetics, Biotechnology, Science Policy, Space Science, 69999 Biological Sciences not elsewhere classified, 39999 Chemical Sciences not elsewhere classified, Brown University, docs directory, regression methods, atomistic calculations, Andrew Peterson, Alireza Khorshidi, Amp, http, open-source package, Atomistic Machine-learning Package v 0.6, mailing list lives, README, energy surface, project lives, GNU General Public License ., Uncategorized, zenodo
Communities
Science and Innovation Policy Studies
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Software . 2017
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software . 2017

Amp: The Atomistic Machine-Learning Package V0.6

Khorshidi, Alireza; Ulissi, Zachary; El Khatib, Muammar; Peterson*, Andrew;