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| || Date || Kickoff meeting: TBA || | || Date || Kickoff meeting: May 9th 2022, 4pm-5pm || |
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| || Room || Kickoff will be online, Zoom link will be posted on ISIS || || ISIS || https://isis.tu-berlin.de/course/view.php?id=27431 (old)|| |
|| Room || Kickoff will be online, Zoom link will be posted on ISIS. Presentations will most likely be in-person at TU Berlin. || || ISIS || https://isis.tu-berlin.de/course/view.php?id=29608|| |
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| This is a research-oriented seminar of about applications of machine learning to quantum chemistry. Students are required to present a selected topic. | 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. |
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| * Generative models for many-particle systems | * Generative models for molecules |
Seminar on Machine Learning for Quantum Chemistry
Date |
Kickoff meeting: May 9th 2022, 4pm-5pm |
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Presentation: TBD |
Room |
Kickoff will be online, Zoom link will be posted on ISIS. Presentations will most likely be in-person at TU Berlin. |
ISIS |
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Trainers |
Stefaan Hessmann, Niklas Gebauer |
Contact |
|
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