Bibliography
[AngMunRah19]
M. Ångqvist, W. A. Muñoz, J. M. Rahm, E. Fransson, C. Durniak, P. Rozyczko, T. H. Rod, and P. Erhart
ICET – A Python Library for Constructing and Sampling Alloy Cluster Expansions
Adv. Theory. Sim. 2, 1900015 (2019)
[EriFraErh19]
Fredrik Eriksson, Erik Fransson, and Paul Erhart
The Hiphive Package for the Extraction of High-Order Force Constants by Machine Learning
Advanced Theory and Simulations 2, 1800184 (2019)
[FraEriErh20]
Erik Fransson, Fredrik Eriksson, and Paul Erhart
Efficient construction of linear models in materials modeling and applications to force constant expansions
npj Computational Materials 6, 135 (2020)
[GolOsh09]
T. Goldstein and S. Osher
The Split Bregman Method for L1-Regularized Problems
SIAM Journal of Imaging Science 2, 323 (2009)
[PedVarGra11]
F. Pedregosa et al.,
Scikit-Learn: Machine Learning in Python,
Journal of Machine Learning Research 12, 2825 (2011)
[MueCed09]
T. Mueller, and G. Ceder
Bayesian approach to cluster expansions
Physical Review B 80, 024103 (2009)
[ZhoSadAbe19]
F. Zhou, B. Sadigh, D. Åberg, Y. Xia, and V. Ozolins
Compressive sensing lattice dynamics. II. Efficient phonon calculations and long-range interactions
Physical Review B 100, 184309 (2019)