| Development of spectral indices for detecting and identifying plant diseases AK Mahlein, T Rumpf, P Welke, HW Dehne, L Plümer, U Steiner, ... Remote Sensing of Environment 128, 21-30, 2013 | 787 | 2013 |
| Harnessing Prior Knowledge for Explainable Machine Learning: An Overview K Beckh, S Müller, M Jakobs, V Toborek, H Tan, R Fischer, P Welke, ... 2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 450-463, 2023 | 81* | 2023 |
| Differentiating smartphone users by app usage P Welke, I Andone, K Blaszkiewicz, A Markowetz Proceedings of the 2016 ACM International Joint Conference on Pervasive and …, 2016 | 74 | 2016 |
| An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning S Müller, V Toborek, K Beckh, M Jakobs, C Bauckhage, P Welke Joint European Conference on Machine Learning and Knowledge Discovery in …, 2023 | 55 | 2023 |
| A generalized weisfeiler-lehman graph kernel TH Schulz, T Horváth, P Welke, S Wrobel Machine Learning 111 (7), 2601-2629, 2022 | 51 | 2022 |
| Retention Is All You Need K Mohiuddin, MA Alam, MM Alam, P Welke, M Martin, J Lehmann, ... Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 49 | 2023 |
| A New Aligned Simple German Corpus V Toborek, M Busch, M Boßert, C Bauckhage, P Welke The 61st Annual Meeting of the Association for Computational Linguistics …, 2023 | 21 | 2023 |
| Graph filtration kernels T Schulz, P Welke, S Wrobel Proceedings of the AAAI Conference on Artificial Intelligence 36 (8), 8196-8203, 2022 | 18 | 2022 |
| On the Necessity of Graph Kernel Baselines T Schulz, P Welke ECML-PKDD, GEM workshop, 2019 | 16 | 2019 |
| Expectation-Complete Graph Representations with Homomorphisms P Welke, M Thiessen, F Jogl, T Gärtner Proceedings of the 40th International Conference on Machine Learning 202 …, 2023 | 14 | 2023 |
| SUSAN: The Structural Similarity Random Walk Kernel J Kalofolias, P Welke, J Vreeken Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 13 | 2021 |
| Weisfeiler and leman go loopy: A new hierarchy for graph representational learning R Paolino, S Maskey, P Welke, G Kutyniok Advances in Neural Information Processing Systems 37, 120780-120831, 2024 | 12 | 2024 |
| Probabilistic frequent subtrees for efficient graph classification and retrieval P Welke, T Horváth, S Wrobel Machine Learning 107 (11), 1847-1873, 2018 | 12 | 2018 |
| Mining tree patterns with partially injective homomorphisms TH Schulz, T Horváth, P Welke, S Wrobel Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 12 | 2018 |
| Ligand affinity prediction with multi-pattern kernels K Ullrich, J Mack, P Welke International Conference on Discovery Science, 474-489, 2016 | 11 | 2016 |
| Logical Distillation of Graph Neural Networks A Pluska, P Welke, T Gärtner, S Malhotra Proceedings of the 21st International Conference on Principles of Knowledge …, 2024 | 10 | 2024 |
| Maximally expressive GNNs for outerplanar graphs F Bause, F Jogl, P Indri, T Drucks, D Penz, NM Kriege, T Gärtner, P Welke, ... Transactions on Machine Learning Research, 2025 | 9 | 2025 |
| Multiple texts as a limiting factor in online learning: quantifying (dis-) similarities of knowledge networks A Mehler, W Hemati, P Welke, M Konca, T Uslu Frontiers in Education 5, 562670, 2020 | 9 | 2020 |
| Probabilistic and exact frequent subtree mining in graphs beyond forests P Welke, T Horváth, S Wrobel Machine Learning 108 (7), 1137-1164, 2019 | 8 | 2019 |
| HOPS: Probabilistic Subtree Mining for Small and Large Graphs P Welke, F Seiffarth, M Kamp, S Wrobel Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020 | 7 | 2020 |
Stefan WrobelFraunhofer IAIS and University of BonnVerified email at iais.fraunhofer.de
