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O. Anatole von Lilienfeld

Identifiers

  • name variant O. Anatole von Lilienfeld 0.60 · backfill

Papers (36)

  1. Approximate Label Symmetries Improve Data Scaling physics.chem-ph · 2026 · author #3
  2. Roadmap on Advancements of the FHI-aims Software Package cond-mat.mtrl-sci · 2025 · author #107
  3. Alchemical normal modes unify chemical space physics.chem-ph · 2018 · author #3
  4. Boosting quantum machine learning models with multi-level combination technique: Pople diagrams revisited physics.chem-ph · 2018 · author #4
  5. Operators in Machine Learning: Response Properties in Chemical Space physics.chem-ph · 2018 · author #3
  6. The fundamentals of quantum machine learning physics.chem-ph · 2018 · author #3
  7. Guest Editorial: Special Topic on Data-enabled Theoretical Chemistry physics.chem-ph · 2018 · author #2
  8. Al$_x$Ga$_{1-x}$As crystals with direct 2 eV band gaps from computational alchemy physics.chem-ph · 2018 · author #2
  9. Alchemical and structural distribution based representation for improved QML physics.chem-ph · 2017 · author #4
  10. Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning physics.chem-ph · 2017 · author #4
  11. Exploring water adsorption on isoelectronically doped graphene using alchemical derivatives physics.chem-ph · 2017 · author #3
  12. Constant Size Molecular Descriptors For Use With Machine Learning physics.chem-ph · 2017 · author #3
  13. Genetic optimization of training sets for improved machine learning models of molecular properties physics.comp-ph · 2016 · author #3
  14. Water on BN doped benzene: A hard test for exchange-correlation functionals and the impact of exact exchange on weak binding physics.chem-ph · 2016 · author #3
  15. Understanding molecular representations in machine learning: The role of uniqueness and target similarity physics.chem-ph · 2016 · author #2
  16. Rapid yet accurate first principle based predictions of alkali halide crystal phases using alchemical perturbation physics.chem-ph · 2016 · author #2
  17. Tuning dissociation using isoelectronically doped graphene and hexagonal boron nitride: water and other small molecules cond-mat.mtrl-sci · 2016 · author #3
  18. Machine Learning, Quantum Mechanics, and Chemical Compound Space physics.chem-ph · 2015 · author #2
  19. Fast and accurate predictions of covalent bonds in chemical space physics.chem-ph · 2015 · author #4
  20. Machine Learning Energies of 2 M Elpasolite (ABC$_2$D$_6$) Crystals physics.chem-ph · 2015 · author #3
  21. Machine learning for many-body physics: efficient solution of dynamical mean-field theory cond-mat.str-el · 2015 · author #2
  22. Water on hexagonal boron nitride from diffusion Monte Carlo cond-mat.mtrl-sci · 2015 · author #4
  23. Machine Learning for Quantum Mechanical Properties of Atoms in Molecules physics.chem-ph · 2015 · author #3
  24. Electronic Spectra from TDDFT and Machine Learning in Chemical Space physics.chem-ph · 2015 · author #4
  25. Crystal Structure Representations for Machine Learning Models of Formation Energies physics.chem-ph · 2015 · author #3
  26. Quantum Mechanical Treatment of Variable Molecular Composition: From "Alchemical" Changes of State Functions to Rational Compound Design physics.chem-ph · 2015 · author #2
  27. Transferable atomic multipole machine learning models for small organic molecules physics.chem-ph · 2015 · author #3
  28. Many Molecular Properties from One Kernel in Chemical Space physics.chem-ph · 2015 · author #2
  29. Machine learning for many-body physics: The case of the Anderson impurity model cond-mat.str-el · 2014 · author #3
  30. Toward transferable interatomic van der Waals interactions without electrons: The role of multipole electrostatics and many-body dispersion physics.chem-ph · 2014 · author #2
  31. Modeling Electronic Quantum Transport with Machine Learning cond-mat.mes-hall · 2014 · author #2
  32. Fourier series of atomic radial distribution functions: A molecular fingerprint for machine learning models of quantum chemical properties physics.chem-ph · 2013 · author #1
  33. Machine Learning of Molecular Electronic Properties in Chemical Compound Space physics.chem-ph · 2013 · author #8
  34. Force correcting atom centered potentials for generalized gradient approximated density functional theory: Approaching hybrid functional accuracy for geometries and harmonic frequencies in small chlorofluorocarbons physics.chem-ph · 2013 · author #1
  35. Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning physics.chem-ph · 2011 · author #4
  36. Coarse-grained interaction potentials for polyaromatic hydrocarbons cond-mat.soft · 2005 · author #1

Mentions

  • 1510.07512 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1509.02847 #4 · backfill · confidence 0.70 O. Anatole von Lilienfeld
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  • 1506.08858 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1505.03291 #4 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1505.00350 #3 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1504.01966 #4 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1503.07406 #3 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1503.07034 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1503.05453 #3 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1502.04563 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1408.1143 #3 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1403.6645 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1401.8277 #2 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 2605.28238 #3 · arxiv_oai · confidence 0.70 O. Anatole von Lilienfeld
  • 1307.2918 #1 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1305.7074 #8 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1301.3225 #1 · backfill · confidence 0.70 O. Anatole von Lilienfeld
  • 1109.2618 #4 · backfill · confidence 0.70 O. Anatole von Lilienfeld

Frequent Coauthors