Franka Bause

I am a Postdoc in the Data Mining and Machine Learning (Machine Learning with Graphs) group at University of Vienna, where I completed my doctorate with distinction 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-organized C'Est La Wien 2023, and the MLG workshop in 2024 and 2025.

Contact

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

Email:
You can send mail to franka.bause[at]univie.ac.at
Office:
Faculty of Computer Science, Research Group Data Mining and Machine Learning
Room 6.01, Währingerstraße 29, 1090 Vienna, Austria

Graph

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]