Dr. Pascal Welke

I do research 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.

Publications

1. Till Schulz and Pascal Welke: On the Necessity of Graph Kernel Baselines, Graph Embedding and Mining Workshop, GEM@ECMLPKDD, 2019
   [paper] [poster] [workshop]
2. Pascal Welke: Frequent Subtree Mining Beyond Forests. Dissertation, University of Bonn, 2019
   [pdf] [slides] [urn] [official publication venue]
3. 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]
   
4. 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]
   
5. 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]
6. 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]
7. 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]
8. 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]
   
9. 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]
   
10. 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]
    
11. 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]
12. 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]
13. 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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