gaybro8777 / cameo_ncomm Goto Github PK

To run the CAMEO simulation code, run the script: FeGaPd_ALBO_200801a.m
All data can be found in the folder "data".
Function dependencies can be found in the folders "Graph Cut mex2.0" and "shared".

% This software was developed by employees of the National Institute of
% Standards and Technology (NIST), an agency of the Federal Government and
% is being made available as a public service. Pursuant to title 17 United
% States Code Section 105, works of NIST employees are not subject to
% copyright protection in the United States.  This software may be subject
% to foreign copyright.  Permission in the United States and in foreign
% countries, to the extent that NIST may hold copyright, to use, copy,
% modify, create derivative works, and distribute this software and its
% documentation without fee is hereby granted on a non-exclusive basis,
% provided that this notice and disclaimer of warranty appears in all
% copies.

% THE SOFTWARE IS PROVIDED 'AS IS' WITHOUT ANY WARRANTY OF ANY KIND, EITHER
% EXPRESSED, IMPLIED, OR STATUTORY, INCLUDING, BUT NOT LIMITED TO, ANY
% WARRANTY THAT THE SOFTWARE WILL CONFORM TO SPECIFICATIONS, ANY IMPLIED
% WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, AND
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% A. Gilad Kusne, NIST, [email protected], Release 8/01/2020
% If using this work for a publication, please cite:
% Kusne, A. Gilad, et al. "On-the-fly Closed-loop Autonomous Materials
% Discovery via Bayesian Active Learning." arXiv preprint arXiv:2006.06141
% (2020).