On (Coalitional) Exchange-Stable Matching. - Jiehua Chen 001; Adrian Chmurovic; Fabian Jogl; Manuel Sorge (SAGT, 2021)

Historian: A Large-Scale Historical Film Dataset with Cinematographic Annotation. - Daniel Helm; Fabian Jogl; Martin Kampel (ICIP, 2022)

Expectation-Complete Graph Representations with Homomorphisms. - Pascal Welke; Maximilian Thiessen; Fabian Jogl; Thomas Gärtner 001 (ICML, 2023)

Expressivity-Preserving GNN Simulation. - Fabian Jogl; Maximilian Thiessen; Thomas Gärtner 001 (NeurIPS, 2023)

The Expressive Power of Path-Based Graph Neural Networks. - Caterina Graziani; Tamara Drucks; Fabian Jogl; Monica Bianchini; Franco Scarselli; Thomas Gärtner 001 (ICML, 2024)

Towards Foundation Models on Graphs: An Analysis on Cross-Dataset Transfer of Pretrained GNNs. - Fabrizio Frasca; Fabian Jogl; Moshe Eliasof; Matan Ostrovsky; Carola-Bibiane Schönlieb; Thomas Gärtner 001; Haggai Maron (CoRR, 2024)

Maximally Expressive GNNs for Outerplanar Graphs. - Franka Bause; Fabian Jogl; Patrick Indri; Tamara Drucks; David Penz; Nils Morten Kriege; Thomas Gärtner 001; Pascal Welke; Maximilian Thiessen (Trans. Mach. Learn. Res., 2025)

Graph Representational Learning: When Does More Expressivity Hurt Generalization? - Sohir Maskey; Raffaele Paolino; Fabian Jogl; Gitta Kutyniok; Johannes F. Lutzeyer (CoRR, 2025)