Greifswald Artificial INtelligence Group
GAIN - Project
We are working in one of the youngest and fastest growing research areas of Machine Learning:
advancing the success of Deep Learning by applying it to data represented as graphs.
Currently, our research focuses on the dynamics and the theory
of Graph Neural Networks (GNNs) as well as their application to power grids and printed circuit boards.
Additionally, we have begun exploring Physics-Informed Neural Networks (PINNs),
aiming to solve increasingly complex differential equations.
Since differential equations provide a powerful framework for modeling phenomena across diverse scientific
domains, and many problems can be modeled as graphs, these topics enable us to apply machine learning to a wide range of interdisciplinary and real-world applications.
The GAIN-group originates from the BMBF-funded GAIN-project (2020-2024), today it centers around the chair of
Machine Learning within the Institute for Data science
at the University of Greifswald.
Enjoy browsing our pages and feel free to contact us via the addresses provided in theContact and Memberssection.
Have fun!