Alexandre Tkatchenko

Получаване на мой собствен потребителски профил

Позовавания

	Всички	От 2018
Позовавания	32843	23318
h-индекс	78	67
i10-индекс	171	158

7000

3500

1750

5250

20102011201220132014201520162017201820192020202120222023142 218 550 848 1375 1572 2107 2393 3193 3623 4710 5066 6026 690

Публичен достъп

Преглед на всички

149 статии

0 статии

налични

неналични

Въз основа на изисквания при финансирането

Съавтори

Klaus-Robert MüllerTU Berlin & Korea University & Google Brain & Max Planck Institute for InformaticsПотвърден имейл адрес: tu-berlin.de
Matthias SchefflerDirector of NOMAD Laboratory at FHI of Max-Planck-Gesellschaft and IRIS-Adlershof of HU BerlinПотвърден имейл адрес: fhi-berlin.mpg.de
O. Anatole von LilienfeldUniversity of Toronto/Vector Institute/Technical University BerlinПотвърден имейл адрес: utoronto.ca
Robert A. DiStasio Jr.Assistant Professor, Chemistry and Chemical Biology, Cornell UniversityПотвърден имейл адрес: cornell.edu
Wei LiuNanjing University of Science and TechnologyПотвърден имейл адрес: njust.edu.cn
Kristof T. SchüttPfizerПотвърден имейл адрес: pfizer.com
Stefan ChmielaTechnische Universität BerlinПотвърден имейл адрес: chmiela.com
Huziel E. SaucedaAssistant Profesor, Instituto de Física, Universidad Nacional Autonoma de MexicoПотвърден имейл адрес: fisica.unam.mx
Igor PoltavskyPostDocПотвърден имейл адрес: uni.lu
Matthias RuppLuxembourg Institute of Science and Technology (LIST)Потвърден имейл адрес: list.lu
alberto ambrosettiUniversità degli Studi di PadovaПотвърден имейл адрес: pd.infn.it
Jan HermannMicrosoft ResearchПотвърден имейл адрес: microsoft.com
Leeor KronikWeizmann Institute of ScienceПотвърден имейл адрес: weizmann.ac.il
Angelos MichaelidesUniversity of CambridgeПотвърден имейл адрес: cam.ac.uk
Noa MaromAssociate Professor, Materials Science and Engineering, Carnegie Mellon UniversityПотвърден имейл адрес: andrew.cmu.edu
Dario AlfeProfessor of Physics at University College London and Universita' di Napoli Federico IIПотвърден имейл адрес: ucl.ac.uk
Reinhard J. MaurerProfessor, Department of Chemistry & Department of Physics, University of WarwickПотвърден имейл адрес: warwick.ac.uk
Johannes HojaUniversity of GrazПотвърден имейл адрес: uni-graz.at
Xinguo RenInstitute of Physics, Chinese Academy of SciencesПотвърден имейл адрес: ustc.edu.cn
Karsten ReuterDirector at Fritz-Haber-Institut der MPGПотвърден имейл адрес: fhi-berlin.mpg.de

Следене

Alexandre Tkatchenko

Professor of Physics, University of Luxembourg; Visiting Professor, TU Berlin

Потвърден имейл адрес: uni.lu - Начална страница

Intermolecular Interactions AI for Science Chemical Physics Materials Physics


Заглавие Сортиране по цитати Сортиране по година Сортиране по заглавие	Позовавания Позовавания	Година
Accurate molecular van der Waals interactions from ground-state electron density and free-atom reference data A Tkatchenko, M Scheffler Physical Review Letters 102 (7), 073005, 2009	5255	2009
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M Rupp, A Tkatchenko, KR Müller, OA von Lilienfeld Physical Review Letters 108, 058301, 2012	1802	2012
Accurate and efficient method for many-body van der Waals interactions A Tkatchenko, RA DiStasio Jr, R Car, M Scheffler Physical Review Letters 108 (23), 236402, 2012	1310	2012
Quantum-chemical insights from deep tensor neural networks KT Schütt, F Arbabzadah, S Chmiela, KR Müller, A Tkatchenko Nature communications 8 (1), 13890, 2017	1120	2017
Reproducibility in density functional theory calculations of solids K Lejaeghere, G Bihlmayer, T Björkman, P Blaha, S Blügel, V Blum, ... Science 351 (6280), aad3000, 2016	1113*	2016
Schnet–a deep learning architecture for molecules and materials KT Schütt, HE Sauceda, PJ Kindermans, A Tkatchenko, KR Müller The Journal of Chemical Physics 148 (24), 241722, 2018	1059	2018
Machine learning of accurate energy-conserving molecular force fields S Chmiela, A Tkatchenko, HE Sauceda, I Poltavsky, KT Schütt, KR Müller Science advances 3 (5), e1603015, 2017	820	2017
Schnet: A continuous-filter convolutional neural network for modeling quantum interactions K Schütt, PJ Kindermans, HE Sauceda Felix, S Chmiela, A Tkatchenko, ... Advances in neural information processing systems 30, 2017	675	2017
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	655	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	616	2013
Resolution-of-identity approach to Hartree–Fock, hybrid density functionals, RPA, MP2 and GW with numeric atom-centered orbital basis functions X Ren, P Rinke, V Blum, J Wieferink, A Tkatchenko, A Sanfilippo, K Reuter, ... New Journal of Physics 14 (5), 053020, 2012	611	2012
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	603	2013
Density-functional theory with screened van der Waals interactions for the modeling of hybrid inorganic-organic systems VG Ruiz, W Liu, E Zojer, M Scheffler, A Tkatchenko Physical Review Letters 108 (14), 146103, 2012	596	2012
Long-range correlation energy calculated from coupled atomic response functions A Ambrosetti, AM Reilly, RA DiStasio Jr, A Tkatchenko The Journal of chemical physics 140 (18), 18A508, 2014	526	2014
Report on the sixth blind test of organic crystal structure prediction methods AM Reilly, RI Cooper, CS Adjiman, S Bhattacharya, AD Boese, ... Acta Crystallographica Section B: Structural Science, Crystal Engineering …, 2016	476	2016
Towards exact molecular dynamics simulations with machine-learned force fields S Chmiela, HE Sauceda, KR Müller, A Tkatchenko Nature communications 9 (1), 3887, 2018	466	2018
First-principles models for van der Waals interactions in molecules and materials: Concepts, theory, and applications J Hermann, RA DiStasio Jr, A Tkatchenko Chemical Reviews 117 (6), 4714-4758, 2017	439	2017
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations B Hourahine, B Aradi, V Blum, F Bonafé, A Buccheri, C Camacho, ... The Journal of chemical physics 152 (12), 124101, 2020	428	2020
Machine learning for molecular simulation F Noé, A Tkatchenko, KR Müller, C Clementi Annual review of physical chemistry 71, 361-390, 2020	393	2020
Machine learning force fields OT Unke, S Chmiela, HE Sauceda, M Gastegger, I Poltavsky, KT Schütt, ... Chemical Reviews 121 (16), 10142-10186, 2021	342	2021

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