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ORCIDPascal Welke
Person information
- affiliation: TU Wien, Machine Learning Research Group, Austria
- affiliation: Lancaster University Leipzig, School of Computing and Communications, Germany
- affiliation (former): University of Bonn, Institute for Computer Science, Germany
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2020 – today
- 2024
[c22]Fouad Alkhoury
, Pascal Welke:
Splitting Stump Forests: Tree Ensemble Compression for Edge Devices. DS (2) 2024: 3-18- [c21]Alexander Pluska, Pascal Welke, Thomas Gärtner, Sagar Malhotra:
Logical Distillation of Graph Neural Networks. KR 2024 - [c20]Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok:
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. NeurIPS 2024 - [i12]Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok:
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. CoRR abs/2403.13749 (2024) - [i11]Alexander Pluska, Pascal Welke, Thomas Gärtner, Sagar Malhotra:
Logical Distillation of Graph Neural Networks. CoRR abs/2406.07126 (2024) - 2023
- [c19]Ramsés J. Sánchez, Lukas Conrads, Pascal Welke, Kostadin Cvejoski, César Ojeda Marin:
Hidden Schema Networks. ACL (1) 2023: 4764-4798 - [c18]Vanessa Toborek, Moritz Busch, Malte Boßert, Christian Bauckhage, Pascal Welke:
A New Aligned Simple German Corpus. ACL (1) 2023: 11393-11412 - [c17]Karishma Mohiuddin, Mirza Ariful Alam, Mirza Mohtashim Alam, Pascal Welke, Michael Martin, Jens Lehmann, Sahar Vahdati:
Retention is All You Need. CIKM 2023: 4752-4758 - [c16]Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner:
Expectation-Complete Graph Representations with Homomorphisms. ICML 2023: 36910-36925 - [c15]Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke:
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. ECML/PKDD (3) 2023: 462-478 - [c14]Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden:
Harnessing Prior Knowledge for Explainable Machine Learning: An Overview. SaTML 2023: 450-463 - [i10]Karishma Mohiuddin, Mirza Ariful Alam, Mirza Mohtashim Alam, Pascal Welke, Michael Martin, Jens Lehmann, Sahar Vahdati:
Retention Is All You Need. CoRR abs/2304.03103 (2023) - [i9]Pascal Welke, Maximilian Thiessen, Fabian Jogl, Thomas Gärtner:
Expectation-Complete Graph Representations with Homomorphisms. CoRR abs/2306.05838 (2023) - [i8]Sebastian Müller, Vanessa Toborek, Katharina Beckh, Matthias Jakobs, Christian Bauckhage, Pascal Welke:
An Empirical Evaluation of the Rashomon Effect in Explainable Machine Learning. CoRR abs/2306.15786 (2023) - 2022
- [j4]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
A generalized Weisfeiler-Lehman graph kernel. Mach. Learn. 111(7): 2601-2629 (2022) - [j3]Dario Antweiler, Marc Harmening, Nicole Marheineke, Andre Schmeißer, Raimund Wegener, Pascal Welke:
Machine learning framework to predict nonwoven material properties from fiber graph representations. Softw. Impacts 14: 100423 (2022) - [c13]Till Hendrik Schulz, Pascal Welke, Stefan Wrobel:
Graph Filtration Kernels. AAAI 2022: 8196-8203 - [c12]Richard Palme, Pascal Welke:
Frequent Generalized Subgraph Mining via Graph Edit Distances. PKDD/ECML Workshops (2) 2022: 477-483 - [i7]Ramsés J. Sánchez, Lukas Conrads, Pascal Welke, Kostadin Cvejoski, César Ojeda:
Hidden Schema Networks. CoRR abs/2207.03777 (2022) - [i6]Vanessa Toborek, Moritz Busch, Malte Boßert, Christian Bauckhage, Pascal Welke:
A New Aligned Simple German Corpus. CoRR abs/2209.01106 (2022) - 2021
- [c11]Janis Kalofolias, Pascal Welke, Jilles Vreeken:
SUSAN: The Structural Similarity Random Walk Kernel. SDM 2021: 298-306 - [e3]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I. Communications in Computer and Information Science 1524, Springer 2021, ISBN 978-3-030-93735-5 [contents] - [e2]Michael Kamp, Irena Koprinska, Adrien Bibal, Tassadit Bouadi, Benoît Frénay, Luis Galárraga, José Oramas, Linara Adilova, Yamuna Krishnamurthy, Bo Kang, Christine Largeron, Jefrey Lijffijt, Tiphaine Viard, Pascal Welke, Massimiliano Ruocco, Erlend Aune, Claudio Gallicchio, Gregor Schiele, Franz Pernkopf, Michaela Blott, Holger Fröning, Günther Schindler, Riccardo Guidotti, Anna Monreale, Salvatore Rinzivillo, Przemyslaw Biecek, Eirini Ntoutsi, Mykola Pechenizkiy, Bodo Rosenhahn, Christopher L. Buckley, Daniela Cialfi, Pablo Lanillos, Maxwell Ramstead, Tim Verbelen, Pedro M. Ferreira, Giuseppina Andresini, Donato Malerba, Ibéria Medeiros, Philippe Fournier-Viger, M. Saqib Nawaz, Sebastián Ventura, Meng Sun, Min Zhou, Valerio Bitetta, Ilaria Bordino, Andrea Ferretti, Francesco Gullo, Giovanni Ponti, Lorenzo Severini, Rita P. Ribeiro, João Gama, Ricard Gavaldà, Lee Cooper, Naghmeh Ghazaleh, Jonas Richiardi, Damian Roqueiro, Diego Saldana Miranda, Konstantinos Sechidis, Guilherme Graça:
Machine Learning and Principles and Practice of Knowledge Discovery in Databases - International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part II. Communications in Computer and Information Science 1525, Springer 2021, ISBN 978-3-030-93732-4 [contents] - [i5]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
A Generalized Weisfeiler-Lehman Graph Kernel. CoRR abs/2101.08104 (2021) - [i4]Katharina Beckh, Sebastian Müller, Matthias Jakobs, Vanessa Toborek, Hanxiao Tan, Raphael Fischer, Pascal Welke, Sebastian Houben, Laura von Rüden:
Explainable Machine Learning with Prior Knowledge: An Overview. CoRR abs/2105.10172 (2021) - [i3]Till Hendrik Schulz, Pascal Welke, Stefan Wrobel:
Graph Filtration Kernels. CoRR abs/2110.11862 (2021) - 2020
- [c10]Pascal Welke:
Efficient Frequent Subgraph Mining in Transactional Databases. DSAA 2020: 307-314 - [c9]Pascal Welke, Fouad Alkhoury, Christian Bauckhage, Stefan Wrobel:
Decision Snippet Features. ICPR 2020: 4260-4267 - [c8]Pascal Welke, Florian Seiffarth, Michael Kamp, Stefan Wrobel:
HOPS: Probabilistic Subtree Mining for Small and Large Graphs. KDD 2020: 1275-1284 - [e1]Daniel Trabold, Pascal Welke, Nico Piatkowski:
Proceedings of the Conference "Lernen, Wissen, Daten, Analysen", Online, September 9-11, 2020. CEUR Workshop Proceedings 2738, CEUR-WS.org 2020 [contents] - [i2]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. CoRR abs/2008.02047 (2020)
2010 – 2019
- 2019
- [b1]Pascal Welke:
Efficient Frequent Subtree Mining Beyond Forests. University of Bonn, Germany, Diss. Artif. Intell. 348, IOS Press 2019, ISBN 978-3-89838-753-8, pp. 1-176 - [j2]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic and exact frequent subtree mining in graphs beyond forests. Mach. Learn. 108(7): 1137-1164 (2019) - 2018
- [j1]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic frequent subtrees for efficient graph classification and retrieval. Mach. Learn. 107(11): 1847-1873 (2018) - [c7]Till Hendrik Schulz, Tamás Horváth, Pascal Welke, Stefan Wrobel:
Mining Tree Patterns with Partially Injective Homomorphisms. ECML/PKDD (2) 2018: 585-601 - 2017
- [i1]Pascal Welke:
Simple Necessary Conditions for the Existence of a Hamiltonian Path with Applications to Cactus Graphs. CoRR abs/1709.01367 (2017) - 2016
- [c6]Pascal Welke, Alexander Markowetz, Torsten Suel, Maria Christoforaki:
Three-hop distance estimation in social graphs. IEEE BigData 2016: 1048-1055 - [c5]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Min-Hashing for Probabilistic Frequent Subtree Feature Spaces. DS 2016: 67-82 - [c4]Katrin Ullrich, Jennifer Mack, Pascal Welke:
Ligand Affinity Prediction with Multi-pattern Kernels. DS 2016: 474-489 - [c3]Pascal Welke, Ionut Andone, Konrad Blaszkiewicz, Alexander Markowetz:
Differentiating smartphone users by app usage. UbiComp 2016: 519-523 - 2015
- [c2]Pascal Welke, Tamás Horváth, Stefan Wrobel:
Probabilistic Frequent Subtree Kernels. NFMCP 2015: 179-193 - 2014
- [c1]Pascal Welke, Tamás Horváth, Stefan Wrobel:
On the Complexity of Frequent Subtree Mining in Very Simple Structures. ILP 2014: 194-209
Coauthor Index
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