Publications

$^*$ Indicates equal contribution.

Conference Publications

Fabian Jogl, Maximilian Thiessen, Thomas Gärtner. 2023.
Expressivity-Preserving GNN Simulation.
In NeurIPS.

Pascal Welke, Maximilian Thiessen, Fabian Jogl, and Thomas Gärtner. 2023.
Expectation-complete graph representations with homomorphisms.
In ICML.

Daniel Helm, Fabian Jogl, and Martin Kampel. 2022.
HISTORIAN: A large-scale historical film dataset with cinematographic annotation.
In ICIP.

Jiehua Chen, Adrian Chmurovic, Fabian Jogl, and Manuel Sorge. 2021.
On (coalitional) exchange-stable matching.
In SAGT.

Peer-Reviewed Workshop Publications and Extended Abstracts

Franka Bause, Fabian Jogl, Patrick Indri, Tamara Drucks, David Penz, Nils Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen. 2023.
Maximally Expressive GNNs for Outerplanar Graphs
In GLFrontiers@NeurIPS accepted as oral.

Andrei Dragos Brasoveanu, Fabian Jogl, Pascal Welke, Maximilian Thiessen. 2023.
Extending Graph Neural Networks with Global Features
In Learning on Graphs conference (extended abstract).

Franka Bause, Fabian Jogl, Pascal Welke, Maximilian Thiessen. 2023.
Maximally Expressive GNNs for Outerplanar Graphs
In Learning on Graphs conference (extended abstract).

Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner. 2022.
Weisfeiler and Leman return with graph transformations.
In Workshop on Mining and Learning with Graphs at ECMLPKDD.

Fabian Jogl, Maximilian Thiessen, and Thomas Gärtner. 2022.
Reducing learning on cell complexes to graphs.
In Workshop on Geometrical and Topological Representation Learning at ICLR.

Jiehua Chen, Adrian Chmurovic, Fabian Jogl, and Manuel Sorge. 2021.
On (coalitional) exchange-stable matching.
In COMSOC.