Articles with public access mandates - Albert P. BartokLearn more
Not available anywhere: 1
Machine-learning approach for one-and two-body corrections to density functional theory: Applications to molecular and condensed water
AP Bartók, MJ Gillan, FR Manby, G Csányi
Physical Review B—Condensed Matter and Materials Physics 88 (5), 054104, 2013
Mandates: UK Engineering and Physical Sciences Research Council
Available somewhere: 35
Gaussian process regression for materials and molecules
VL Deringer, AP Bartók, N Bernstein, DM Wilkins, M Ceriotti, G Csányi
Chemical Reviews 121 (16), 10073-10141, 2021
Mandates: Swiss National Science Foundation, US Department of Defense, UK Engineering …
Machine learning unifies the modeling of materials and molecules
AP Bartók, S De, C Poelking, N Bernstein, JR Kermode, G Csányi, ...
Science advances 3 (12), e1701816, 2017
Mandates: Swiss National Science Foundation, US Department of Defense, UK Engineering …
Machine learning a general-purpose interatomic potential for silicon
AP Bartók, J Kermode, N Bernstein, G Csányi
Physical Review X 8 (4), 041048, 2018
Mandates: US Department of Energy, US Department of Defense, UK Engineering and …
Physics-inspired structural representations for molecules and materials
F Musil, A Grisafi, AP Bartók, C Ortner, G Csányi, M Ceriotti
Chemical Reviews 121 (16), 9759-9815, 2021
Mandates: Swiss National Science Foundation
Modeling molecular interactions in water: From pairwise to many-body potential energy functions
GA Cisneros, KT Wikfeldt, L Ojamäe, J Lu, Y Xu, H Torabifard, AP Bartók, ...
Chemical reviews 116 (13), 7501-7528, 2016
Mandates: US National Science Foundation, US Department of Energy, US National …
Accuracy and transferability of Gaussian approximation potential models for tungsten
WJ Szlachta, AP Bartók, G Csányi
Physical Review B 90 (10), 104108, 2014
Mandates: UK Engineering and Physical Sciences Research Council
Realistic atomistic structure of amorphous silicon from machine-learning-driven molecular dynamics
VL Deringer, N Bernstein, AP Bartók, MJ Cliffe, RN Kerber, LE Marbella, ...
The journal of physical chemistry letters 9 (11), 2879-2885, 2018
Mandates: US Department of Defense, UK Engineering and Physical Sciences Research Council
Regularized SCAN functional
AP Bartók, JR Yates
The Journal of chemical physics 150 (16), 2019
Mandates: UK Engineering and Physical Sciences Research Council, UK Science and …
Incompleteness of atomic structure representations
SN Pozdnyakov, MJ Willatt, AP Bartók, C Ortner, G Csányi, M Ceriotti
Physical Review Letters 125 (16), 166001, 2020
Mandates: Swiss National Science Foundation
Roadmap on machine learning in electronic structure
HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ...
Electronic Structure 4 (2), 023004, 2022
Mandates: US Department of Energy, Natural Sciences and Engineering Research Council …
Determining pressure-temperature phase diagrams of materials
RJN Baldock, LB Pártay, AP Bartók, MC Payne, G Csányi
Physical Review B 93 (17), 174108, 2016
Mandates: UK Engineering and Physical Sciences Research Council
Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of
H Muhli, X Chen, AP Bartók, P Hernández-León, G Csányi, T Ala-Nissila, ...
Physical Review B 104 (5), 054106, 2021
Mandates: Academy of Finland
First-principles energetics of water clusters and ice: A many-body analysis
MJ Gillan, D Alfè, AP Bartók, G Csányi
The Journal of chemical physics 139 (24), 2013
Mandates: UK Engineering and Physical Sciences Research Council
Nested sampling for materials: The case of hard spheres
LB Pártay, AP Bartók, G Csányi
Physical Review E 89 (2), 022302, 2014
Mandates: UK Engineering and Physical Sciences Research Council
Combining phonon accuracy with high transferability in Gaussian approximation potential models
J George, G Hautier, AP Bartók, G Csányi, VL Deringer
The Journal of Chemical Physics 153 (4), 2020
Mandates: UK Engineering and Physical Sciences Research Council, European Commission
Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water
D Alfè, AP Bartók, G Csányi, MJ Gillan
The Journal of Chemical Physics 138 (22), 2013
Mandates: UK Engineering and Physical Sciences Research Council
Elucidation of the structural and optical properties of metal cation (Na+, K+, and Bi 3+) incorporated Cs 2 AgInCl 6 double perovskite nanocrystals
P Vashishtha, BE Griffith, Y Fang, A Jaiswal, GV Nutan, AP Bartók, ...
Journal of Materials Chemistry A 10 (7), 3562-3578, 2022
Mandates: UK Biotechnology and Biological Sciences Research Council, UK Engineering …
Gaussian approximation potentials: Theory, software implementation and application examples
S Klawohn, JP Darby, JR Kermode, G Csányi, MA Caro, AP Bartók
The Journal of Chemical Physics 159 (17), 2023
Mandates: Academy of Finland, UK Engineering and Physical Sciences Research Council …
Polytypism in the ground state structure of the Lennard-Jonesium
LB Pártay, C Ortner, AP Bartók, CJ Pickard, G Csányi
Physical Chemistry Chemical Physics 19 (29), 19369-19376, 2017
Mandates: UK Engineering and Physical Sciences Research Council, European Commission
Publication and funding information is determined automatically by a computer program