Machine Learning for First Principles Observables

CECAM Flagship Workshop

  • Start: Jul 8, 2024
  • End: Jul 12, 2024
  • Location: Zuse Institute, Takustraße 7, 14195, Berlin
  • Host: Elena Gelzinyte, Angela Harper, Simone Köcher, Hanna Türk
Machine Learning for First Principles Observables
The countdown has begun for the upcoming CECAM Flagship Workshop: "Machine Learning for First Principles Observables", which will take place from the 8th to the 12th of June at the Zuse Institute, Takustraße 7, 14195, Berlin. The workshop is organized by members of the Institute´s Theory Department and further supported by CECAM, Psi-K, and DFG.

Machine Learning methods have recently found widespread use in areas of atomistic modelling, mainly focusing on developing surrogate models for the potential energy surface with superior computational efficiency while retaining first principles accuracy. However, approaches to learn observable properties directly are just emerging and are challenged by several issues, which we intend to address in the workshop. The event is meant to support the development of a new collaborative, international network connecting different fields of research and integrating the young researchers community with the help of a scientifically diverse, interactive workshop.

The workshop topics include:

- ML of electron density and Hamiltonians

- ML of electronic observables

- ML of mechanical & magnetic observables

- ML of spectroscopic observables

- ML of reaction networks

- Theoretical and experimental databases

Registration deadline: 19th April 2024.

We invite abstract submissions for contributed talks (20 min) and posters. Online screening of the talks will be available with registration. For further details and registration, see CECAM Website.

If you have any questions, please do not hesitate to contact Simone Köcher at

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