On the Complexity of Frequent Subtree Mining in Very Simple Structures. - Pascal Welke; Tamás Horváth 001; Stefan Wrobel (ILP, 2014)

Probabilistic Frequent Subtree Kernels. - Pascal Welke; Tamás Horváth 001; Stefan Wrobel (NFMCP, 2015)

Three-hop distance estimation in social graphs. - Pascal Welke; Alexander Markowetz; Torsten Suel; Maria Christoforaki (IEEE BigData, 2016)

Ligand Affinity Prediction with Multi-pattern Kernels. - Katrin Ullrich; Jennifer Mack; Pascal Welke (DS, 2016)

Min-Hashing for Probabilistic Frequent Subtree Feature Spaces. - Pascal Welke; Tamás Horváth 001; Stefan Wrobel (DS, 2016)

Differentiating smartphone users by app usage. - Pascal Welke; Ionut Andone; Konrad Blaszkiewicz; Alexander Markowetz (UbiComp, 2016)

Simple Necessary Conditions for the Existence of a Hamiltonian Path with Applications to Cactus Graphs. - Pascal Welke (CoRR, 2017)

Mining Tree Patterns with Partially Injective Homomorphisms. - Till Hendrik Schulz; Tamás Horváth 001; Pascal Welke; Stefan Wrobel (ECML/PKDD (2), 2018)

Probabilistic frequent subtrees for efficient graph classification and retrieval. - Pascal Welke; Tamás Horváth 001; Stefan Wrobel (Mach. Learn., 2018)

Probabilistic and exact frequent subtree mining in graphs beyond forests. - Pascal Welke; Tamás Horváth 001; Stefan Wrobel (Mach. Learn., 2019)

Efficient Frequent Subtree Mining Beyond Forests. - Pascal Welke (IOS Press, 2019)

Efficient Frequent Subgraph Mining in Transactional Databases. - Pascal Welke (DSAA, 2020)

Decision Snippet Features. - Pascal Welke; Fouad Alkhoury; Christian Bauckhage; Stefan Wrobel (ICPR, 2020)

HOPS: Probabilistic Subtree Mining for Small and Large Graphs. - Pascal Welke; Florian Seiffarth; Michael Kamp; Stefan Wrobel (KDD, 2020)

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

SUSAN: The Structural Similarity Random Walk Kernel. - Janis Kalofolias; Pascal Welke; Jilles Vreeken (SDM, 2021)

Explainable Machine Learning with Prior Knowledge: An Overview. - Katharina Beckh; Sebastian Müller; Matthias Jakobs; Vanessa Toborek; Hanxiao Tan; Raphael Fischer 001; Pascal Welke; Sebastian Houben; Laura von Rüden (CoRR, 2021)

Graph Filtration Kernels. - Till Hendrik Schulz; Pascal Welke; Stefan Wrobel (AAAI, 2022)

Frequent Generalized Subgraph Mining via Graph Edit Distances. - Richard Palme; Pascal Welke (PKDD/ECML Workshops (2), 2022)

Hidden Schema Networks. - Ramsés J. Sánchez; Lukas Conrads; Pascal Welke; Kostadin Cvejoski; César Ojeda (CoRR, 2022)

A generalized Weisfeiler-Lehman graph kernel. - Till Hendrik Schulz; Tamás Horváth 001; Pascal Welke; Stefan Wrobel (Mach. Learn., 2022)

Machine learning framework to predict nonwoven material properties from fiber graph representations. - Dario Antweiler; Marc Harmening; Nicole Marheineke; Andre Schmeißer; Raimund Wegener; Pascal Welke (Softw. Impacts, 2022)

Hidden Schema Networks. - Ramsés J. Sánchez; Lukas Conrads; Pascal Welke; Kostadin Cvejoski; César Ojeda Marin (ACL (1), 2023)

A New Aligned Simple German Corpus. - Vanessa Toborek; Moritz Busch; Malte Boßert; Christian Bauckhage; Pascal Welke (ACL (1), 2023)

Retention is All You Need. - Karishma Mohiuddin; Mirza Ariful Alam; Mirza Mohtashim Alam; Pascal Welke; Michael Martin 001; Jens Lehmann 001; Sahar Vahdati (CIKM, 2023)

Expectation-Complete Graph Representations with Homomorphisms. - Pascal Welke; Maximilian Thiessen; Fabian Jogl; Thomas Gärtner 001 (ICML, 2023)

An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. - Sebastian Müller; Vanessa Toborek; Katharina Beckh; Matthias Jakobs; Christian Bauckhage; Pascal Welke (ECML/PKDD (3), 2023)

Harnessing Prior Knowledge for Explainable Machine Learning: An Overview. - Katharina Beckh; Sebastian Müller; Matthias Jakobs; Vanessa Toborek; Hanxiao Tan; Raphael Fischer 001; Pascal Welke; Sebastian Houben; Laura von Rüden (SaTML, 2023)

Splitting Stump Forests: Tree Ensemble Compression for Edge Devices. - Fouad Alkhoury; Pascal Welke (DS (2), 2024)

Logical Distillation of Graph Neural Networks. - Alexander Pluska; Pascal Welke; Thomas Gärtner 001; Sagar Malhotra (KR, 2024)

Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. - Raffaele Paolino; Sohir Maskey; Pascal Welke; Gitta Kutyniok (NeurIPS, 2024)

Maximally Expressive GNNs for Outerplanar Graphs. - Franka Bause; Fabian Jogl; Patrick Indri; Tamara Drucks; David Penz; Nils Morten Kriege; Thomas Gärtner 001; Pascal Welke; Maximilian Thiessen (Trans. Mach. Learn. Res., 2025)

Expressive Pooling for Graph Neural Networks. - Veronica Lachi; Alice Moallemy-Oureh; Andreas Roth; Pascal Welke (Trans. Mach. Learn. Res., 2025)

WILTing Trees: Interpreting the Distance Between MPNN Embeddings. - Masahiro Negishi; Thomas Gärtner 001; Pascal Welke (CoRR, 2025)