Pascal Welke

According to our database, Pascal Welke authored at least 30 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning.

Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok

CoRR, 2024

Logical Distillation of Graph Neural Networks.

Alexander Pluska, Pascal Welke, Thomas Gärtner, Sagar Malhotra

Proceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning, 2024

2023

Harnessing Prior Knowledge for Explainable Machine Learning: An Overview.

Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning.

Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

Expectation-Complete Graph Representations with Homomorphisms.

Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner

Proceedings of the International Conference on Machine Learning, 2023

Retention is All You Need.

Karishma Mohiuddin, Mirza Ariful Alam, Mirza Mohtashim Alam, Pascal Welke, Michael Martin, Jens Lehmann, Sahar Vahdati

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

A New Aligned Simple German Corpus.

Vanessa Toborek, Moritz Busch, Malte Boßert, Christian Bauckhage, Pascal Welke

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Hidden Schema Networks.

Ramsés J. Sánchez, Lukas Conrads, Pascal Welke, Kostadin Cvejoski, César Ojeda Marin

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

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, December, 2022

A generalized Weisfeiler-Lehman graph kernel.

Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel

Mach. Learn., 2022

Hidden Schema Networks.

Ramsés J. Sánchez, Lukas Conrads, Pascal Welke, Kostadin Cvejoski, César Ojeda

CoRR, 2022

Frequent Generalized Subgraph Mining via Graph Edit Distances.

Richard Palme, Pascal Welke

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2022

Graph Filtration Kernels.

Till Hendrik Schulz, Pascal Welke, Stefan Wrobel

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Explainable Machine Learning with Prior Knowledge: An Overview.

Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden

CoRR, 2021

SUSAN: The Structural Similarity Random Walk Kernel.

Janis Kalofolias, Pascal Welke, Jilles Vreeken

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

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

HOPS: Probabilistic Subtree Mining for Small and Large Graphs.

Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Decision Snippet Features.

Pascal Welke, Fouad Alkhoury, Christian Bauckhage, Stefan Wrobel

Proceedings of the 25th International Conference on Pattern Recognition, 2020

Efficient Frequent Subgraph Mining in Transactional Databases.

Pascal Welke

Proceedings of the 7th IEEE International Conference on Data Science and Advanced Analytics, 2020

2019

Efficient Frequent Subtree Mining Beyond Forests.

Pascal Welke

PhD thesis, 2019

Probabilistic and exact frequent subtree mining in graphs beyond forests.

Pascal Welke, Tamás Horváth, Stefan Wrobel

Mach. Learn., 2019

2018

Probabilistic frequent subtrees for efficient graph classification and retrieval.

Pascal Welke, Tamás Horváth, Stefan Wrobel

Mach. Learn., 2018

Mining Tree Patterns with Partially Injective Homomorphisms.

Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2018

2017

Simple Necessary Conditions for the Existence of a Hamiltonian Path with Applications to Cactus Graphs.

Pascal Welke

CoRR, 2017

2016

Differentiating smartphone users by app usage.

Pascal Welke, Ionut Andone, Konrad Blaszkiewicz, Alexander Markowetz

Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, 2016

Min-Hashing for Probabilistic Frequent Subtree Feature Spaces.

Pascal Welke, Tamás Horváth, Stefan Wrobel

Proceedings of the Discovery Science - 19th International Conference, 2016

Ligand Affinity Prediction with Multi-pattern Kernels.

Katrin Ullrich, Jennifer Mack, Pascal Welke

Proceedings of the Discovery Science - 19th International Conference, 2016

Three-hop distance estimation in social graphs.

Pascal Welke, Alexander Markowetz, Torsten Suel, Maria Christoforaki

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

Probabilistic Frequent Subtree Kernels.

Pascal Welke, Tamás Horváth, Stefan Wrobel

Proceedings of the New Frontiers in Mining Complex Patterns - 4th International Workshop, 2015

2014

On the Complexity of Frequent Subtree Mining in Very Simple Structures.

Pascal Welke, Tamás Horváth, Stefan Wrobel

Proceedings of the Inductive Logic Programming - 24th International Conference, 2014