Standout Papers

Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons 2010 2026 2015 2020 2.0k
  1. Gaussian Approximation Potentials: The Accuracy of Quantum Mechanics, without the Electrons (2010)
    Albert P. Bartók, M. C. Payne et al. Physical Review Letters
  2. On representing chemical environments (2013)
    Albert P. Bartók, Risi Kondor et al. Physical Review B
  3. Gaussian Process Regression for Materials and Molecules (2021)
    Volker L. Deringer, Albert P. Bartók et al. Chemical Reviews
  4. Machine Learning Interatomic Potentials as Emerging Tools for Materials Science (2019)
    Volker L. Deringer, A. Miguel et al. Advanced Materials
  5. Performance and Cost Assessment of Machine Learning Interatomic Potentials (2020)
    Yunxing Zuo, Chi Chen et al. The Journal of Physical Chemistry A
  6. Comparing molecules and solids across structural and alchemical space (2016)
    Sandip De, Albert P. Bartók et al. Physical Chemistry Chemical Physics
  7. Machine learning unifies the modeling of materials and molecules (2017)
    Albert P. Bartók, Sandip De et al. Science Advances
  8. Machine learning based interatomic potential for amorphous carbon (2017)
    Volker L. Deringer, Gábor Cśanyi Physical review. B.
  9. Gaussian approximation potentials: A brief tutorial introduction (2015)
    Albert P. Bartók, Gábor Cśanyi International Journal of Quantum Chemistry
  10. Modeling Molecular Interactions in Water: From Pairwise to Many-Body Potential Energy Functions (2016)
    G. Andrés Cisneros, Kjartan Thor Wikfeldt et al. Chemical Reviews
  11. Origins of structural and electronic transitions in disordered silicon (2021)
    Volker L. Deringer, Noam Bernstein et al. Nature
  12. The design space of E(3)-equivariant atom-centred interatomic potentials (2025)
    Simon Batzner, Dávid Péter Kovács et al. Nature Machine Intelligence
  13. MACE-OFF: Short-Range Transferable Machine Learning Force Fields for Organic Molecules (2025)
    Dávid Péter Kovács, J. Harry Moore et al. Journal of the American Chemical Society

Immediate Impact

6 by Nobel laureates 13 from Science/Nature 182 standout
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Citing Papers

Hydrogen Embrittlement as a Conspicuous Material Challenge─Comprehensive Review and Future Directions
2024 Standout
Structural disorder determines capacitance in nanoporous carbons
2024 StandoutScience

Works of Gábor Cśanyi being referenced

Machine Learning Interatomic Potentials as Emerging Tools for Materials Science
2019 Standout
Towards an atomistic understanding of disordered carbon electrode materials
2018
and 2 more

Author Peers

Author Last Decade Papers Cites
Gábor Cśanyi 14020 3096 3529 168 17.2k
Jörg Behler 12518 4106 3375 116 14.9k
Alexandre Tkatchenko 16398 8486 4093 234 24.8k
O. Anatole von Lilienfeld 8041 2830 4327 115 10.6k
Olexandr Isayev 7254 1107 3978 95 10.2k
Michele Ceriotti 6294 3751 2024 165 10.4k
Stefan Goedecker 10003 7032 835 158 18.2k
Rampi Ramprasad 10864 879 1930 295 15.2k
Bartosz A. Grzybowski 12969 2210 1791 356 29.2k
Albert P. Bartók 6687 1586 2035 50 8.0k
Volker L. Deringer 10794 1550 900 139 14.3k

All Works

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2026