Franka Bause

I am a Postdoc in the Relational Machine Learning Lab of Rebekka Burkholz at CISPA Helmholtz Center for Information Security. I completed my doctorate with distinction in the Data Mining and Machine Learning (Machine Learning with Graphs) group at University of Vienna in 2025.
I completed both my Bachelor’s and Master’s degrees at TU Dortmund University, graduating with honors in 2020. Throughout my studies, I gained valuable experience working as a research and teaching assistant.
My research mostly centers around graph learning and similarity measures for graphs, with the aim of improving both efficiency and accuracy.
I co-organize the GLOW (Graph Learning on Wednesdays) reading group, as well as C'Est La Wien 2023, and the MLG workshop in 2024, 2025, and 2026.

You can find my CV somewhere on this page.

Contact

I have accounts on Google Scholar, Github, and LinkedIn.

Email:
You can send mail to franka.bause[at]cispa.de
Office:
Relational Machine Learning Lab, CISPA Helmholtz Center for Information Security
Room 0.06, Im Oberen Werk 1, St. Ingbert, 66386 Germany

Graph

News

Mar '26 We'll be organizing the 23rd International Workshop on Mining and Learning with Graphs at ECML/PKDD in Naples. Submit your work until June 5th!
Mar '26 Joining the organizing team of GLOW (Graph Learning on Wednesdays).
Feb '26 I joined the Relational Machine Learning Lab of Rebekka Burkholz at CISPA Helmholtz Center for Information Security!
Dec '25 I received the Award of Excellence from the Austrian Ministry of Women, Science and Research for my dissertation (see here for photos)!

Old News
Sep '25 We organized the 22nd International Workshop on Mining and Learning with Graphs at ECML/PKDD in Porto.
Aug '25 I successfully defended my doctoral thesis on Efficient and Expressive Graph Learning.
Jun '25 I got awarded the "Best of the Best"-Award in the category Publications in highest ranking venues 2024 from the faculty of computer science!
May '25 Happy to announce that we'll be organizing the 22nd International Workshop on Mining and Learning with Graphs at ECML/PKDD in Porto. Submit your work until June 14th!
Mar '25 Finally set up this website!

Publications

  1. Franka Bause*, Fabian Jogl*, Patrick Indri, Tamara Drucks, David Penz, Nils M. Kriege, Thomas Gärtner, Pascal Welke, Maximilian Thiessen (2025):
    Maximally Expressive GNNs for Outerplanar Graphs.
    Transactions on Machine Learning Research (TMLR)

    [pdf] [poster] [slides] [video] [code] [reviews] [journal]

  2. Lorenz Kummer, Samir Moustafa, Anatol Ehrlich, Franka Bause, Nikolaus Suess, Wilfried N. Gansterer, Nils M. Kriege (2025):
    Weisfeiler and Leman Go Gambling: Why Expressive Lottery Tickets Win.
    Forty-second International Conference on Machine Learning

    [pdf] [code] [reviews]

  3. Franka Bause, Samir Moustafa, Johannes Langguth, Wilfried N. Gansterer, Nils M. Kriege (2024):
    On the Two Sides of Redundancy in Graph Neural Networks.
    Machine Learning and Knowledge Discovery in Databases. Research Track

    [pdf] [code]

  4. Franka Bause*, Christian Permann*, Nils M. Kriege (2024):
    Approximating the Graph Edit Distance with Compact Neighborhood Representations.
    Machine Learning and Knowledge Discovery in Databases. Research Track

    [pdf] [poster] [code]

  5. Andreas Roth, Franka Bause, Nils M. Kriege, Thomas Liebig (2024):
    Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph.
    The Third Learning on Graphs Conference

    [pdf] [poster] [code] [reviews]

  6. Franka Bause, Nils M. Kriege (2022):
    Gradual Weisfeiler-Leman: Slow and Steady Wins the Race.
    Learning on Graphs Conference

    [pdf] [poster] [code]

  7. Franka Bause, Erich Schubert, Nils M. Kriege (2022):
    EmbAssi: embedding assignment costs for similarity search in large graph databases.
    Data Min. Knowl. Discov. (36)

    [pdf] [poster] [code]

  8. Franka Bause, David B. Blumenthal, Erich Schubert, Nils M. Kriege (2021):
    Metric Indexing for Graph Similarity Search.
    Similarity Search and Applications - 14th International Conference

    [pdf] [poster] [video]

  9. Christopher Morris, Nils M. Kriege, Franka Bause, Kristian Kersting, Petra Mutzel, Marion Neumann (2020):
    TUDataset: A collection of benchmark datasets for learning with graphs.
    ICML 2020 Workshop on Graph Representation Learning and Beyond (GRL+ 2020)

    [pdf]

  10. Nils M. Kriege, Pierre-Louis Giscard, Franka Bause, Richard C. Wilson (2019):
    Computing Optimal Assignments in Linear Time for Approximate Graph Matching.
    2019 IEEE International Conference on Data Mining (ICDM)

    [pdf]