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The role of feature space in atomistic learning
v1v2v3v4 (latest)

The role of feature space in atomistic learning

6 September 2020
Alexander Goscinski
Guillaume Fraux
G. Imbalzano
Michele Ceriotti
ArXiv (abs)PDFHTML

Papers citing "The role of feature space in atomistic learning"

6 / 6 papers shown
Completeness of Atomic Structure Representations
Completeness of Atomic Structure RepresentationsAPL Machine Learning (AML), 2023
M. J. Willatt
Sergey Pozdnyakov
Christoph Ortner
Michele Ceriotti
432
19
0
28 Feb 2023
A smooth basis for atomistic machine learning
A smooth basis for atomistic machine learningJournal of Chemical Physics (JCP), 2022
Filippo Bigi
Kevin K. Huguenin-Dumittan
Michele Ceriotti
D. Manolopoulos
270
9
0
05 Sep 2022
Optimal radial basis for density-based atomic representations
Optimal radial basis for density-based atomic representationsJournal of Chemical Physics (JCP), 2021
Alexander Goscinski
Félix Musil
Sergey Pozdnyakov
Michele Ceriotti
253
19
0
18 May 2021
Ranking the information content of distance measures
Ranking the information content of distance measuresPNAS Nexus (PNAS Nexus), 2021
Aldo Glielmo
C. Zeni
Bing Cheng
Gábor Csányi
Alessandro Laio
443
52
0
30 Apr 2021
Improving Sample and Feature Selection with Principal Covariates
  Regression
Improving Sample and Feature Selection with Principal Covariates Regression
Rose K. Cersonsky
B. Helfrecht
Edgar A. Engel
Michele Ceriotti
144
40
0
22 Dec 2020
Representations of molecules and materials for interpolation of
  quantum-mechanical simulations via machine learning
Representations of molecules and materials for interpolation of quantum-mechanical simulations via machine learningnpj Computational Materials (npj Comput Mater), 2020
Marcel F. Langer
Alex Goessmann
M. Rupp
AI4CE
280
113
0
26 Mar 2020
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