Scientific Machine Learning (SciML) is a growing field in which methods and techniques from machine learning and scientific computing coalesce. SciML spans across the scientific domains of the CDS, and it is the goal of the SciML Lab to bring together CDS scientists to share their expertise, collaborate on new projects, and foster the research on scientific machine learning.
The name Scientific Machine Learning was coined in January 2018 at a US Department of Energy (DOE) Basic Research Needs workshop; see www.osti.gov/biblio/1478744.
Courses offered in SS 2024
[Lecture] Deep Learning (Prof. Dr. G. Frahling)
[Lecture] Mathematics of Data Science – An Introduction (Dr. J. Weber)
[Seminar] Trustworthy Machine Learning (Prof. Dr. A. Bojchevski)
[Seminar] Methods of Mathematical Modeling in Life Sciences (PD Dr. T. Mrziglod)
[Seminar] Machine Learning (Dr. Z. Nikolić)
[Practical Course] Interactive Visualization in Research and Application (Prof. Dr.-Ing. Tatiana von Landesberger)