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O. Anatole von Lilienfeld

Orcid: 0000-0001-7419-0466

Affiliations:
  • University of Toronto, Canada
  • National Center for Computational Design and Discovery of Novel Materials (MARVEL), Basel, Switzerland
  • University of Basel, Department of Chemistry, Switzerland
  • Argonne National Laboratory, Lemont, IL, USA


According to our database1, O. Anatole von Lilienfeld authored at least 12 papers between 2012 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

2012
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2016
2018
2020
2022
2024
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Legend:

Book 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
Data-Error Scaling in Machine Learning on Natural Discrete Combinatorial Mutation-prone Sets: Case Studies on Peptides and Small Molecules.
[BibTeX]
[DOI]
Vanni Doffini
,
O. Anatole von Lilienfeld
,
Michael A. Nash
CoRR, 2024

2023
Improved decision making with similarity based machine learning: applications in chemistry.
[BibTeX]
[DOI]
Dominik Lemm
,
Guido Falk von Rudorff
,
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., December, 2023

Encrypted machine learning of molecular quantum properties.
[BibTeX]
[DOI]
Jan Weinreich
,
Guido Falk von Rudorff
,
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., June, 2023

2021
An assessment of the structural resolution of various fingerprints commonly used in machine learning.
[BibTeX]
[DOI]
Behnam Parsaeifard
,
Deb Sankar De
,
Anders S. Christensen
,
Felix A. Faber
,
Emir Kocer
,
Sandip De
,
Jörg Behler
,
O. Anatole von Lilienfeld
,
Stefan Goedecker
Mach. Learn. Sci. Technol., 2021

2020
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.
[BibTeX]
[DOI]
Julia Westermayr
,
Felix A. Faber
,
Anders S. Christensen
,
O. Anatole von Lilienfeld
,
Philipp Marquetand
Mach. Learn. Sci. Technol., 2020

Thousands of reactants and transition states for competing E2 and S$_\mathrm{N}$2 reactions.
[BibTeX]
[DOI]
Guido Falk von Rudorff
,
Stefan N. Heinen
,
Marco Bragato
,
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., 2020

Introducing Machine Learning: Science and Technology.
[BibTeX]
[DOI]
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., 2020

Machine learning the computational cost of quantum chemistry.
[BibTeX]
[DOI]
Stefan N. Heinen
,
Max Schwilk
,
Guido Falk von Rudorff
,
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., 2020

On the role of gradients for machine learning of molecular energies and forces.
[BibTeX]
[DOI]
Anders S. Christensen
,
O. Anatole von Lilienfeld
Mach. Learn. Sci. Technol., 2020

Wasserstein metric for improved quantum machine learning with adjacency matrix representations.
[BibTeX]
[DOI]
Onur Çaylak
,
O. Anatole von Lilienfeld
,
Björn Baumeier
Mach. Learn. Sci. Technol., 2020

2012
Modeling of molecular atomization energies using machine learning.
[BibTeX]
[DOI]
Matthias Rupp
,
Alexandre Tkatchenko
,
Klaus-Robert Müller
,
O. Anatole von Lilienfeld
J. Cheminformatics, 2012

Learning Invariant Representations of Molecules for Atomization Energy Prediction.
[BibTeX]
[DOI]
Grégoire Montavon
,
Katja Hansen
,
Siamac Fazli
,
Matthias Rupp
,
Franziska Biegler
,
Andreas Ziehe
,
Alexandre Tkatchenko
,
O. Anatole von Lilienfeld
,
Klaus-Robert Müller
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012


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