O. Anatole von Lilienfeld

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Alexandre TkatchenkoProfessor of Physics, University of Luxembourg; Visiting Professor, TU Berlin; APS Fellow; FRSCAdresse e-mail validée de uni.lu
Matthias RuppLuxembourg Institute of Science and Technology (LIST)Adresse e-mail validée de list.lu
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, GermanyAdresse e-mail validée de tu-berlin.de
Raghunathan RamakrishnanTata Institute of Fundamental Research Hyderabad, IndiaAdresse e-mail validée de tifrh.res.in
Guido Falk von RudorffDepartment of Chemistry, University KasselAdresse e-mail validée de uni-kassel.de
Huang BingWuhan UniversityAdresse e-mail validée de whu.edu.cn
Felix Andreas FaberResearcher in Data Science and Modelling, AstraZenecaAdresse e-mail validée de astrazeneca.com
Ursula RothlisbergerProfessor of Computational Chemistry and BiochemistryAdresse e-mail validée de epfl.ch
Anders S. ChristensenQuantum Consulting by ChristensenAdresse e-mail validée de unibas.ch
Ivano TavernelliIBM Quantum, IBM Research - ZurichAdresse e-mail validée de zurich.ibm.com
Stefan HeinenPostdoc, Empa, High Performance Ceramics LabAdresse e-mail validée de empa.ch
Pavlo O. DralProfessor, Xiamen UniversityAdresse e-mail validée de xmu.edu.cn
Daniel SebastianiProfessor of Theoretical Chemistry, University Halle, GermanyAdresse e-mail validée de chemie.uni-halle.de
Grégoire MontavonGuest professor, Freie Universität BerlinAdresse e-mail validée de fu-berlin.de
Mark E TuckermanNew York UniversityAdresse e-mail validée de nyu.edu
Louis-Francois ArsenaultColumbia universityAdresse e-mail validée de columbia.edu
Dominik LemmDepartment of Physics, University of ViennaAdresse e-mail validée de univie.ac.at
Alejandro Lopez-BezanillaStaff Scientist at Los Alamos Nat'l LabAdresse e-mail validée de lanl.gov
Mauricio D. Coutinho-NetoUniversidade Federal do ABCAdresse e-mail validée de ufabc.edu.br
Rickard ArmientoLinköping UniversityAdresse e-mail validée de liu.se

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O. Anatole von Lilienfeld

Clark & CIFAR AI chair at University of Toronto/Vector Institute/Technical University Berlin

Adresse e-mail validée de utoronto.ca - Page d'accueil

computational physics theoretical chemistry quantum machine learning density functional theory chemical space


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
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	2551	2012
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	2150	2014
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	905	2015
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	890	2015
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	807	2013
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	733*	2017
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	725	2013
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	663	2004
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	516	2015
Long range interactions in nanoscale science RH French, VA Parsegian, R Podgornik, RF Rajter, A Jagota, J Luo, ... Reviews of Modern Physics 82 (2), 1887-1944, 2010	490	2010
Machine Learning Energies of 2 Million Elpasolite Crystals FA Faber, A Lindmaa, OA Von Lilienfeld, R Armiento Physical review letters 117 (13), 135502, 2016	481	2016
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	433	2018
Exploring chemical compound space with quantum-based machine learning OA von Lilienfeld, KR Müller, A Tkatchenko Nature Reviews Chemistry 4 (7), 347-358, 2020	349	2020
Retrospective on a decade of machine learning for chemical discovery OA von Lilienfeld, K Burke Nature communications 11 (1), 4895, 2020	343	2020
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	337	2020
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	335	2016
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	315	2015
Quantum machine learning in chemical compound space OA Von Lilienfeld Angewandte Chemie International Edition 57 (16), 4164-4169, 2018	271	2018
Machine learning for quantum mechanical properties of atoms in molecules M Rupp, R Ramakrishnan, OA Von Lilienfeld The Journal of Physical Chemistry Letters 6 (16), 3309-3313, 2015	258	2015
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	255	2015

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