| 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 | 480 | 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), 241717, 2018 | 436 | 2018 |
| 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 | 337 | 2020 |
| 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 | 148 | 2020 |
| 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 | 140 | 2019 |
| 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 | 137 | 2019 |
| 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 | 96* | 2017 |
| 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 | 87 | 2020 |
| 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 | 84 | 2021 |
| # COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol A Dommer, L Casalino, F Kearns, M Rosenfeld, N Wauer, SH Ahn, ... The international journal of high performance computing applications 37 (1 …, 2023 | 80 | 2023 |
| Informing geometric deep learning with electronic interactions to accelerate quantum chemistry Z Qiao, AS Christensen, M Welborn, FR Manby, A Anandkumar, ... Proceedings of the National Academy of Sciences 119 (31), e2205221119, 2022 | 79 | 2022 |
| 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 | 70 | 2021 |
| 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 | 70 | 2021 |
| 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 | 63 | 2015 |
| 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 | 63 | 2014 |
| 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 | 48 | 2013 |
| 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 | 45 | 2020 |
| 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 | 40 | 2015 |
| 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 3, 2021 | 36 | 2021 |
| Machine Learning Models of Vibrating H2CO: Comparing Reproducing Kernels, FCHL, and PhysNet S Käser, D Koner, AS Christensen, OA von Lilienfeld, M Meuwly The Journal of Physical Chemistry A 124 (42), 8853-8865, 2020 | 32 | 2020 |
O. Anatole von LilienfeldClark & CIFAR AI chair at University of Toronto/Vector Institute/Technical University Berlinایمیل تأیید شده در utoronto.ca
