Publications & Presentations

Publications

Peer-Reviewed

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).

Preprints

Mathematics

• 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

• Taha, D. (2022). Symmetric Spaces for Machine Learning – Representation Matters! (Project Report). STRUCTURES NEWSletter. https://structures.uni-heidelberg.de/news/STRUCTURES_Newsletter_2022_Dec.pdf

Expository

• Taha, D. (2022). HEGL: The Heidelberg Experimental Geometry Lab. STRUCTURES Newsletter. https://structures.uni-heidelberg.de/news/STRUCTURES_Newsletter_2022_Apr.pdf

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.