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O. Anatole von Lilienfeld
O. Anatole von Lilienfeld
Clark & CIFAR AI chair at University of Toronto/Vector Institute/Technical University Berlin
Bestätigte E-Mail-Adresse bei utoronto.ca - Startseite
Titel
Zitiert von
Zitiert von
Jahr
Fast and accurate modeling of molecular atomization energies with machine learning
M Rupp, A Tkatchenko, KR Müller, OA Von Lilienfeld
Physical review letters 108 (5), 058301, 2012
20292012
Quantum chemistry structures and properties of 134 kilo molecules
R Ramakrishnan, PO Dral, M Rupp, OA Von Lilienfeld
Scientific data 1 (1), 1-7, 2014
14092014
Machine learning predictions of molecular properties: Accurate many-body potentials and nonlocality in chemical space
K Hansen, F Biegler, R Ramakrishnan, W Pronobis, OA Von Lilienfeld, ...
The journal of physical chemistry letters 6 (12), 2326-2331, 2015
7462015
Big data meets quantum chemistry approximations: the Δ-machine learning approach
R Ramakrishnan, PO Dral, M Rupp, OA Von Lilienfeld
Journal of chemical theory and computation 11 (5), 2087-2096, 2015
6832015
Machine learning of molecular electronic properties in chemical compound space
G Montavon, M Rupp, V Gobre, A Vazquez-Mayagoitia, K Hansen, ...
New Journal of Physics 15 (9), 095003, 2013
6722013
Assessment and validation of machine learning methods for predicting molecular atomization energies
K Hansen, G Montavon, F Biegler, S Fazli, M Rupp, M Scheffler, ...
Journal of Chemical Theory and Computation 9 (8), 3404-3419, 2013
6412013
Optimization of effective atom centered potentials for London dispersion forces in density functional theory
OA Von Lilienfeld, I Tavernelli, U Rothlisberger, D Sebastiani
Physical review letters 93 (15), 153004, 2004
6372004
Prediction errors of molecular machine learning models lower than hybrid DFT error
FA Faber, L Hutchison, B Huang, J Gilmer, SS Schoenholz, GE Dahl, ...
Journal of chemical theory and computation 13 (11), 5255-5264, 2017
5832017
Long range interactions in nanoscale science
RH French, VA Parsegian, R Podgornik, RF Rajter, A Jagota, J Luo, ...
Reviews of Modern Physics 82 (2), 1887, 2010
4442010
Machine Learning Energies of 2 Million Elpasolite Crystals
FA Faber, A Lindmaa, OA Von Lilienfeld, R Armiento
Physical review letters 117 (13), 135502, 2016
4172016
Crystal structure representations for machine learning models of formation energies
F Faber, A Lindmaa, OA Von Lilienfeld, R Armiento
International Journal of Quantum Chemistry 115 (16), 1094-1101, 2015
4072015
Alchemical and structural distribution based representation for universal quantum machine learning
FA Faber, AS Christensen, B Huang, OA Von Lilienfeld
The Journal of chemical physics 148 (24), 2018
3642018
Communication: Understanding molecular representations in machine learning: The role of uniqueness and target similarity
B Huang, OA Von Lilienfeld
The Journal of Chemical Physics 145 (16), 2016
2962016
FCHL revisited: Faster and more accurate quantum machine learning
AS Christensen, LA Bratholm, FA Faber, O Anatole von Lilienfeld
The Journal of chemical physics 152 (4), 2020
2412020
Retrospective on a decade of machine learning for chemical discovery
OA von Lilienfeld, K Burke
Nature communications 11 (1), 4895, 2020
2362020
Collective many-body van der Waals interactions in molecular systems
RA DiStasio Jr, OA von Lilienfeld, A Tkatchenko
Proceedings of the National Academy of Sciences 109 (37), 14791-14795, 2012
2362012
Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties
OA Von Lilienfeld, R Ramakrishnan, M Rupp, A Knoll
International Journal of Quantum Chemistry 115 (16), 1084-1093, 2015
2342015
Two-and three-body interatomic dispersion energy contributions to binding in molecules and solids
O Anatole von Lilienfeld, A Tkatchenko
The Journal of chemical physics 132 (23), 2010
2332010
Quantum machine learning in chemical compound space
OA Von Lilienfeld
Angewandte Chemie International Edition 57 (16), 4164-4169, 2018
2312018
Electronic spectra from TDDFT and machine learning in chemical space
R Ramakrishnan, M Hartmann, E Tapavicza, OA Von Lilienfeld
The Journal of chemical physics 143 (8), 2015
2262015
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