Scientific Machine Learning for Simulations
(in German: Scientific Machine Learning for Simulations - )
Module-ID: FIN-INF-999958 |
| Link: | LSF |
| Responsibility: | Prof. Dr. Christian Lessig |
| Lecturer: | Prof. Dr. Christian Lessig |
| Classes: |
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| Applicability in curriculum: | - M.Sc. INF: Informatik - M.Sc. INGINF: Informatik - M.Sc. WIF: Informatik - M.Sc. DKE: Learning Methods and Models for Data Science - M.Sc. DE: Methoden der Informatik - M.Sc. VC: Visual Computing |
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Abbreviation SMLfS |
Credit Points 5 |
Semester Winter |
Term ab 1. |
Duration 1 Semester |
Language english |
Level Master |
Intended learning outcomes:
- kennen und verstehen spezialisierte Fachinhalte, die das Bachelor-Studium erweitern und vertiefen
- können sich neues Wissen eigenständig aneignen und für sich nutzbar mache
- können selbstständig wissenschaftlich arbeiten
- können Wissen vermitteln, Ergebnisse erklären und Argumente verteidigen
Content:
Application of neural networks for the simulation of physical systems (and simulations in general)Mathematical analysis of neural networks, with a focus on simulations
Workload:
5 Credit Points = 150 h (28h Präsenzzeit + 122h selbstständige Arbeit)
| Type of examination: | Teaching method / lecture hours per week (SWS): |
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Presentation (potentially also results of implementation) |
Seminar (2 SWS) |
| Prerequisites according to examination regulations: | Recommended prerequisites: |
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none |
Recommended: Introductory course on neural networks, Scientific Computing I and II (or similar courses on numerics of ODEs and PDEs |
| Media: | Literature: |
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Board, slides, computer code |
Will be announced at the beginning of the term. |
Comments: