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ORCIDO. Anatole von Lilienfeld
Person information
- affiliation: University of Toronto, Canada
- affiliation: National Center for Computational Design and Discovery of Novel Materials (MARVEL), Basel, Switzerland
- affiliation: University of Basel, Department of Chemistry, Switzerland
- affiliation: Argonne National Laboratory, Lemont, IL, USA
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2020 – today
- 2023
[j10]Jan Weinreich
, Guido Falk von Rudorff, O. Anatole von Lilienfeld:
Encrypted machine learning of molecular quantum properties. Mach. Learn. Sci. Technol. 4(2): 25017 (2023)- [j9]Dominik Lemm, Guido Falk von Rudorff, O. Anatole von Lilienfeld:
Improved decision making with similarity based machine learning: applications in chemistry. Mach. Learn. Sci. Technol. 4(4): 45043 (2023) - 2022
- [i1]Jan Weinreich, Guido Falk von Rudorff, O. Anatole von Lilienfeld:
Encrypted machine learning of molecular quantum properties. CoRR abs/2212.04322 (2022) - 2021
- [j8]Behnam Parsaeifard, Deb Sankar De, Anders S. Christensen, Felix A. Faber, Emir Kocer, Sandip De, Jörg Behler, O. Anatole von Lilienfeld, Stefan Goedecker:
An assessment of the structural resolution of various fingerprints commonly used in machine learning. Mach. Learn. Sci. Technol. 2(1): 15018 (2021) - 2020
- [j7]O. Anatole von Lilienfeld:
Introducing Machine Learning: Science and Technology. Mach. Learn. Sci. Technol. 1(1): 10201 (2020) - [j6]Stefan N. Heinen, Max Schwilk, Guido Falk von Rudorff, O. Anatole von Lilienfeld:
Machine learning the computational cost of quantum chemistry. Mach. Learn. Sci. Technol. 1(2): 25002 (2020) - [j5]Julia Westermayr, Felix A. Faber, Anders S. Christensen, O. Anatole von Lilienfeld, Philipp Marquetand:
Neural networks and kernel ridge regression for excited states dynamics of CH2NH$_2^+$: From single-state to multi-state representations and multi-property machine learning models. Mach. Learn. Sci. Technol. 1(2): 25009 (2020) - [j4]Onur Çaylak, O. Anatole von Lilienfeld, Björn Baumeier:
Wasserstein metric for improved quantum machine learning with adjacency matrix representations. Mach. Learn. Sci. Technol. 1(3): 03 (2020) - [j3]Anders S. Christensen, O. Anatole von Lilienfeld:
On the role of gradients for machine learning of molecular energies and forces. Mach. Learn. Sci. Technol. 1(4): 45018 (2020) - [j2]Guido Falk von Rudorff, Stefan N. Heinen, Marco Bragato, O. Anatole von Lilienfeld:
Thousands of reactants and transition states for competing E2 and S$_\mathrm{N}$2 reactions. Mach. Learn. Sci. Technol. 1(4): 45026 (2020)
2010 – 2019
- 2012
- [j1]Matthias Rupp, Alexandre Tkatchenko, Klaus-Robert Müller, O. Anatole von Lilienfeld:
Modeling of molecular atomization energies using machine learning. J. Cheminformatics 4(S-1): 33 (2012) - [c1]Grégoire Montavon, Katja Hansen, Siamac Fazli, Matthias Rupp, Franziska Biegler, Andreas Ziehe, Alexandre Tkatchenko, O. Anatole von Lilienfeld, Klaus-Robert Müller:
Learning Invariant Representations of Molecules for Atomization Energy Prediction. NIPS 2012: 449-457
Coauthor Index
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