Dr. Pascal Welke

I am interested in Data Mining, Applied Graph Theory, Machine Learning, and Human-computer Interaction. I wrote my PhD thesis on 'Probabilistic Frequent Subtree Mining'.

I also teach several courses that are offered by our group in the Bachelors program and Masters program in Computer Science and I supervise BA and MA theses.

Contact

University of Bonn:

Room 1.027, Endenicher Allee 19a, 53115 Bonn. Phone: +49 228 73 4514

email: 

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Other:

I have an account on ResearchGate.  My publications are indexed by dblp.
You can give me anonymous feedback (for example on my teaching performance).

Publications

1. Dario Antweiler, Pascal Welke:
   Temporal Graph Analysis for Outbreak Pattern Detection in COVID-19 Contact Tracing Networks.
   Machine Learning in Public Health Workshop, MLPH@NeurIPS, 2020 (accepted).
   

   [preprint] [slides] [workshop]

2. Pascal Welke:
   Efficient Frequent Subgraph Mining in Transactional Databases.
   IEEE International Conference on Data Science and Advanced Analytics, DSAA, 2020.
   

   [preprint] [video] [slides] [doi] [conference]

3. Pascal Welke, Fouad Alkhoury, Christian Bauckhage, Stefan Wrobel:
   Decision Snippet Features.
   International Conference on Pattern Recognition, ICPR, (accepted), 2021.
   

   [preprint] [doi] [conference]

4. Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel:
   HOPS: Probabilistic Subtree Mining for Small and Large Graphs.
   ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD, 2020.
   

   [preprint] [short video] [slides] [video] [doi] [dblp] [conference]

5. Alexander Mehler, Wahed Hemati, Pascal Welke, Maxim Konca, Tolga Uslu:
   Multiple Texts as a Limiting Factor in Online Learning: Quantifying (Dis-)similarities of Knowledge Networks across Languages.
   Frontiers in Education | Digital Education, 2020.
   

   [preprint] [doi] [dblp] [arXiv] [journal]

6. Till Schulz, Pascal Welke:
   On the Necessity of Graph Kernel Baselines.
   Graph Embedding and Mining Workshop, GEM@ECMLPKDD 2019
   

   [paper] [poster] [workshop]

7. Pascal Welke:
   Frequent Subtree Mining Beyond Forests.
   Dissertations in Artificial Intelligence Vol. 348, IOS Press, 2019
   

   [book] [pdf] [slides] [urn] [official publication venue]

8. Pascal Welke, Tamas Horvath, Stefan Wrobel:
   Probabilistic and Exact Frequent Subtree Mining in Graphs Beyond Forests.
   Machine Learning, Volume 108, Issue 7, 2019
   

   [preprint] [doi] [read-only free official version] [journal]

9. Pascal Welke, Tamas Horvath, Stefan Wrobel:
   Probabilistic Frequent Subtrees for Efficient Graph Classification and Retrieval.
   Machine Learning, Volume 107, Issue 11, Springer 2018.
   

   [preprint] [dblp] [doi] [read-only free official version] [journal]

10. Till Hendrik Schulz, Tamas Horvath, Pascal Welke, Stefan Wrobel:
    Mining Tree Patterns with Partially Injective Homomorphisms.
    European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML/PKDD 2018, Springer LNCS 11052.
    

    [preprint] [slides] [dblp] [doi] [conference]

11. Pascal Welke, Alexander Markowetz, Torsten Suel, Maria Christoforaki:
    3-Hop Distance Estimation in Social Graphs.
    IEEE International Conference on Big Data, BigData 2016, IEEE 2016.
    

    [preprint] [slides] [dblp] [doi] [conference]

12. Pascal Welke, Tamas Horvath, Stefan Wrobel:
    Min-Hashing for Probabilistic Frequent Subtree Feature Spaces.
    Proceedings of Discovery Science - 18th International Conference, DS 2016, Springer LNAI 9956.
    

    [preprint] [slides] [poster] [dblp] [doi] [conference]

13. Katrin Ullrich, Jennifer Mack, Pascal Welke:
    Ligand Affinity Prediction with Multi-Pattern Kernels.
    Proceedings of Discovery Science - 18th International Conference, DS 2016, Springer LNAI 9956.
    

    [preprint] [slides] [dblp] [doi] [conference]
    

14. Pascal Welke, Ionut Andone, Konrad Blaskiewicz, Alexander Markowetz:
    Differentiating Smartphone Users by App Usage.
    Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, UbiComp 2016, ACM 2016.
    

    [preprint] [slides] [dblp] [doi] [conference]

15. Pascal Welke, Tamas Horvath, Stefan Wrobel:
    Probabilistic Frequent Subtree Kernels.
    Proceedings of the Fourth Workshop on New Frontiers in Mining Complex Patterns, nfMCP 2015, Selected Extended Papers, Springer LNCS 9607.

    [preprint] [slides] [dblp] [doi] [workshop]
    

16. Pascal Welke:
    Simple Necessary Conditions for the Existence of a Hamiltonian Path with Applications to Cactus Graphs.
    CoRR abs/1709.01367.
    

    [preprint] [slides] [arXiv] [workshop]

17. Pascal Welke, Tamas Horvath, Stefan Wrobel:
    On the Complexity of Frequent Subtree Mining in Very Simple Structures.
    Proceedings of the Inductive Logic Programming Conference, ILP 2014, Springer LNCS 9046.
    

    [preprint] [slides] [dblp] [doi] [conference]

18. Anne-Kathrin Mahlein, Till Rumpf, Pascal Welke, Heinz-Wilhelm Dehne, Lutz Plümer, Ulrike Steiner, Erich-Christian Oerke:
    Development of spectral indices for detecting and identifying plant diseases.
    Remote Sensing of Environment Volume 128, Elsevier 2013.
    

    [doi] [journal]

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