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Seminar on Machine Learning for Quantum Chemistry

Date

Kickoff meeting: Tuesday, May 2nd 2023, 16:15-17:00

Presentations: Wednesday, July 5th, 14:00 (tentative)

Room

MAR 4.033 or Zoom: https://tu-berlin.zoom.us/j/65745322054?pwd=c1YxaFVGelRPUzVvNjBmbk80U1hNZz09

ISIS

https://isis.tu-berlin.de/course/view.php?id=33513

Trainers

Stefaan Hessmann, Niklas Gebauer

Contact

stefaan.hessmann@tu-berlin.de, n.gebauer@tu-berlin.de

Credits

3 ECTS, Elective in the modules "Machine Learning I", "Machine Learning II", and "Cognitive Algorithms"

This is a research-oriented seminar about applications of machine learning to quantum chemistry. There is no formal registration for the kick-off meeting. In the general case, it is not possible to take the seminar as a standalone course.

Students will read, understand, evaluate and present selected research papers on machine learning methods in quantum chemistry. At the end of the semester, each student will present their topic in a 20 min talk (+ 10 min questions) in English.

For a list of available research papers, please refer to the ISIS course linked above.

The available topics cover

  • Representations of molecules and materials
  • Encoding prior knowledge and symmetries in ML models
  • Solving the Schrödinger equation with ML
  • ML for molecular dynamics
  • Generative models for molecules

IDA Wiki: Main/SS23_MLQc (last edited 2023-04-20 14:40:35 by NiklasGebauer)