Takip et
Anders S. Christensen
Anders S. Christensen
Quantum Consulting by Christensen
unibas.ch üzerinde doğrulanmış e-posta adresine sahip - Ana Sayfa
Başlık
Alıntı yapanlar
Alıntı yapanlar
Yıl
Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications
AS Christensen, T Kubař, Q Cui, M Elstner
Chemical reviews 116 (9), 5301-5337, 2016
2812016
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), 241717, 2018
2732018
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), 044107, 2020
1402020
Operators in quantum machine learning: Response properties in chemical space
AS Christensen, FA Faber, OA von Lilienfeld
The Journal of Chemical Physics 150 (6), 064105, 2019
812019
A universal density matrix functional from molecular orbital-based machine learning: Transferability across organic molecules
L Cheng, M Welborn, AS Christensen, TF Miller III
The Journal of Chemical Physics 150 (13), 131103, 2019
802019
QML: A Python toolkit for quantum machine learning
AS Christensen, FA Faber, B Huang, LA Bratholm, A Tkatchenko, ...
URL https://github. com/qmlcode/qml, 2017
592017
Improving intermolecular interactions in DFTB3 using extended polarization from chemical-potential equalization
AS Christensen, M Elstner, Q Cui
The Journal of chemical physics 143 (8), 084123, 2015
512015
PHAISTOS: A framework for Markov Chain Monte Carlo simulation and inference of protein structure
W Boomsma, J Frellsen, T Harder, S Bottaro, KE Johansson, P Tian, ...
Journal of computational chemistry 34 (19), 1697-1705, 2013
422013
Neural networks and kernel ridge regression for excited states dynamics of CH2NH: From single-state to multi-state representations and multi-property machine learning models
J Westermayr, FA Faber, AS Christensen, OA von Lilienfeld, ...
Machine Learning: Science and Technology 1 (2), 025009, 2020
382020
A third-generation dispersion and third-generation hydrogen bonding corrected PM6 method: PM6-D3H+
JC Kromann, AS Christensen, C Steinmann, M Korth, JH Jensen
PeerJ 2, e449, 2014
372014
DFTB3 parametrization for copper: the importance of orbital angular momentum dependence of hubbard parameters
M Gaus, H Jin, D Demapan, AS Christensen, P Goyal, M Elstner, Q Cui
Journal of chemical theory and computation 11 (9), 4205-4219, 2015
332015
On the role of gradients for machine learning of molecular energies and forces
AS Christensen, OA von Lilienfeld
Machine Learning: Science and Technology 1 (4), 045018, 2020
312020
An assessment of the structural resolution of various fingerprints commonly used in machine learning
B Parsaeifard, DS De, AS Christensen, FA Faber, E Kocer, S De, J Behler, ...
Machine Learning: Science and Technology 2 (1), 015018, 2021
292021
Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics
AS Christensen, TE Linnet, M Borg, W Boomsma, K Lindorff-Larsen, ...
PLoS One 8 (12), e84123, 2013
252013
Interface of the polarizable continuum model of solvation with semi-empirical methods in the GAMESS program
C Steinmann, KL Blædel, AS Christensen, JH Jensen
PloS one 8 (7), e67725, 2013
212013
Definitive benchmark study of ring current effects on amide proton chemical shifts
AS Christensen, SPA Sauer, JH Jensen
Journal of Chemical Theory and Computation 7 (7), 2078-2084, 2011
212011
Unite: Unitary n-body tensor equivariant network with applications to quantum chemistry
Z Qiao, AS Christensen, M Welborn, FR Manby, A Anandkumar, ...
arXiv preprint arXiv:2105.14655, 2021
172021
Charge and exciton transfer simulations using machine-learned Hamiltonians
M Krämer, PM Dohmen, W Xie, D Holub, AS Christensen, M Elstner
Journal of chemical theory and computation 16 (7), 4061-4070, 2020
172020
Towards a barrier height benchmark set for biologically relevant systems
JC Kromann, AS Christensen, Q Cui, JH Jensen
PeerJ 4, e1994, 2016
172016
OrbNet Denali: A machine learning potential for biological and organic chemistry with semi-empirical cost and DFT accuracy
AS Christensen, SK Sirumalla, Z Qiao, MB O’Connor, DGA Smith, F Ding, ...
The Journal of Chemical Physics 155 (20), 204103, 2021
152021
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