Albert P. Bartok
Albert P. Bartok
Verified email at warwick.ac.uk
TitleCited byYear
Gaussian approximation potentials: The accuracy of quantum mechanics, without the electrons
AP Bartók, MC Payne, R Kondor, G Csányi
Physical review letters 104 (13), 136403, 2010
6982010
On representing chemical environments
AP Bartók, R Kondor, G Csányi
Physical Review B 87 (18), 184115, 2013
4922013
Comparing molecules and solids across structural and alchemical space
S De, AP Bartók, G Csányi, M Ceriotti
Physical Chemistry Chemical Physics 18 (20), 13754-13769, 2016
2152016
G aussian approximation potentials: A brief tutorial introduction
AP Bartók, G Csányi
International Journal of Quantum Chemistry 115 (16), 1051-1057, 2015
1832015
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
1742017
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 Bartok, ...
Chemical reviews 116 (13), 7501-7528, 2016
1642016
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 88 (5), 054104, 2013
1272013
Accuracy and transferability of Gaussian approximation potential models for tungsten
WJ Szlachta, AP Bartók, G Csányi
Physical Review B 90 (10), 104108, 2014
1182014
Efficient sampling of atomic configurational spaces
LB Pártay, AP Bartók, G Csányi
The Journal of Physical Chemistry B 114 (32), 10502-10512, 2010
742010
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
632018
Machine learning a general-purpose interatomic potential for silicon
AP Bartók, J Kermode, N Bernstein, G Csányi
Physical Review X 8 (4), 041048, 2018
602018
Computer simulation of the 13 crystalline phases of ice
A Baranyai, A Bartók, AA Chialvo
The Journal of chemical physics 123 (5), 054502, 2005
392005
First-principles energetics of water clusters and ice: A many-body analysis
MJ Gillan, D Alfč, AP Bartók, G Csányi
The Journal of chemical physics 139 (24), 244504, 2013
382013
First-principles energetics of water clusters and ice: A many-body analysis
MJ Gillan, D Alfč, AP Bartók, G Csányi
The Journal of chemical physics 139 (24), 244504, 2013
382013
Communication: Energy benchmarking with quantum Monte Carlo for water nano-droplets and bulk liquid water
D Alfč, AP Bartók, G Csányi, MJ Gillan
The Journal of chemical physics 138 (22), 221102, 2013
302013
Limitations of the rigid planar nonpolarizable models of water
A Baranyai, A Bartók, AA Chialvo
The Journal of chemical physics 124 (7), 074507, 2006
302006
Nested sampling for materials: The case of hard spheres
LB Pártay, AP Bartók, G Csányi
Physical Review E 89 (2), 022302, 2014
282014
Structural and thermodynamic properties of different phases of supercooled liquid water
P Jedlovszky, LB Pártay, AP Bartók, VP Voloshin, NN Medvedev, ...
The Journal of chemical physics 128 (24), 244503, 2008
282008
Determining pressure-temperature phase diagrams of materials
RJN Baldock, LB Pártay, AP Bartók, MC Payne, G Csányi
Physical Review B 93 (17), 174108, 2016
272016
On the re-engineered TIP4P water models for the prediction of vapor–liquid equilibrium
AA Chialvo, A Bartók, A Baranyai
Journal of molecular liquids 129 (1-2), 120-124, 2006
212006
The system can't perform the operation now. Try again later.
Articles 1–20