Publications & Presentations



Machine Learning

  • Zhao, W., Lopez, F., Riestenberg, J. M., Strube, M., Taha, D., & Trettel, S. J. (2023). Modeling Graphs Beyond Hyperbolic: Graph Neural Networks in Symmetric Positive Definite Matrices. Paper accepted for publication at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD).



  • Albers, P., Lander, F., & Westermann, J. (In preparation). More on Polygonal symplectic billiards.
  • Albers, P., Aretz, P., & Seifert, I. (2023). Families of periodic delay orbits. arXiv preprint arXiv:2304.07550.

Non-Peer Reviewed

Machine Learning


Conference Presentations

  • Taha, D. (2023). Mathematics and Visualization in Action: A Selection of Student Projects from the Heidelberg Experimental Geometry Lab. Abstract accepted for presentation at the “MathArt” Minisymposium, DMV Annual Meeting.