Martin Ritzert

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Martin GroheProfessor of Computer Science, RWTH Aachen UniversityVerified email at informatik.rwth-aachen.de
Jan TönshoffPhD Student, RWTH Aachen UniversityVerified email at informatik.rwth-aachen.de
Jan Eric LenssenMax Planck Institute for Informatics, Kumo.aiVerified email at mpi-inf.mpg.de
Christopher MorrisRWTH Aachen UniversityVerified email at cs.rwth-aachen.de
Matthias FeyFounding Engineer @ kumo.aiVerified email at tu-dortmund.de
William L HamiltonAssistant Professor of Computer Science, McGill University and MilaVerified email at cs.mcgill.ca
Gaurav RattanAssistant Professor, University of TwenteVerified email at utwente.nl
Kasper Green LarsenProfessor, Computer Science, Aarhus UniversityVerified email at cs.au.dk
Jan G. RittigRWTH Aachen University, Aachener Verfahrenstechnik, Lehrstuhl für SystemverfahrenstechnikVerified email at rwth-aachen.de
Manuel DahmenIEK-10 Energy Systems Engineering at Forschungszentrum JülichVerified email at fz-juelich.de
Alexander MitsosAVT Systemverfahrenstechnik, RWTH Aachen University and Energy Systems Engineering IEK-10Verified email at alum.mit.edu
Jana Marie WeberAssistant professor, TU DelftVerified email at tudelft.nl
Artur M. SchweidtmannDelft University of Technology, Department of Chemical EngineeringVerified email at tudelft.nl
Tobias SchumacherUniversity of MannheimVerified email at uni-mannheim.de
Markus StrohmaierUniversity of Mannheim, GESIS - Leibniz Institute for the Social Sciences, CSH ViennaVerified email at uni-mannheim.de
Florian LemmerichUniversity of PassauVerified email at lemmerich.net
Steffen van BergeremHumboldt-Universität zu BerlinVerified email at informatik.hu-berlin.de
Christof LödingInformatik, RWTH AachenVerified email at cs.rwth-aachen.de
Mikael Møller HøgsgaardAarhus UniversityVerified email at cs.au.dk

Martin Ritzert

Georg-August Universität Göttingen

Verified email at informatik.uni-goettingen.de

Theoretical Machine Learning Graph Learning Algorithms Complexity Logic


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Weisfeiler and leman go neural: Higher-order graph neural networks C Morris, M Ritzert, M Fey, WL Hamilton, JE Lenssen, G Rattan, M Grohe Proceedings of the AAAI Conference on Artificial Intelligence 33, 4602-4609, 2019	1768	2019
Graph neural networks for maximum constraint satisfaction J Toenshoff, M Ritzert, H Wolf, M Grohe Frontiers in artificial intelligence 3, 98, 2021	54	2021
Graph Learning with 1D Convolutions on Random Walks J Toenshoff, M Ritzert, H Wolf, M Grohe arXiv preprint arXiv:2102.08786, 2021	44	2021
Learning first-order definable concepts over structures of small degree M Grohe, M Ritzert 2017 32nd Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 1-12, 2017	34	2017
Where Did the Gap Go? Reassessing the Long-Range Graph Benchmark J Tönshoff, M Ritzert, E Rosenbluth, M Grohe arXiv preprint arXiv:2309.00367, 2023	26	2023
The effects of randomness on the stability of node embeddings T Schumacher, H Wolf, M Ritzert, F Lemmerich, M Grohe, M Strohmaier Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021	23	2021
Learning MSO-definable hypotheses on strings M Grohe, C Löding, M Ritzert International Conference on Algorithmic Learning Theory, 434-451, 2017	19	2017
Graph machine learning for design of high‐octane fuels JG Rittig, M Ritzert, AM Schweidtmann, S Winkler, JM Weber, P Morsch, ... AIChE Journal 69 (4), e17971, 2023	17	2023
RUN-CSP: Unsupervised Learning of Message Passing Networks for Binary Constraint Satisfaction Problems J Toenshoff, M Ritzert, H Wolf, M Grohe arXiv preprint arXiv:1909.08387, 2019	17	2019
Walking out of the weisfeiler leman hierarchy: Graph learning beyond message passing J Tönshoff, M Ritzert, H Wolf, M Grohe Transactions on Machine Learning Research, 2023	7	2023
Optimal weak to strong learning K Green Larsen, M Ritzert Advances in Neural Information Processing Systems 35, 32830-32841, 2022	7	2022
On the Parameterized Complexity of Learning First-Order Logic S van Bergerem, M Grohe, M Ritzert Proceedings of the 41st ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of …, 2022	7	2022
Learning Definable Hypotheses on Trees E Grienenberger, M Ritzert 22nd International Conference on Database Theory (ICDT 2019), 2019	6	2019
Distinguished In Uniform: Self Attention Vs. Virtual Nodes E Rosenbluth, J Tönshoff, M Ritzert, B Kisin, M Grohe arXiv preprint arXiv:2405.11951, 2024	5	2024
Adaboost is not an optimal weak to strong learner MM Høgsgaard, KG Larsen, M Ritzert International Conference on Machine Learning, 13118-13140, 2023	3	2023
On the Parameterized Complexity of Learning Logic S van Bergerem, M Grohe, M Ritzert CoRR, 2021	2	2021
Boosting, Voting Classifiers and Randomized Sample Compression Schemes A da Cunha, KG Larsen, M Ritzert arXiv preprint arXiv:2402.02976, 2024	1	2024
Transformers vs. Message Passing GNNs: Distinguished in Uniform J Tönshoff, E Rosenbluth, M Ritzert, B Kisin, M Grohe The Twelfth International Conference on Learning Representations, 2023		2023
AdaBoost is not an Optimal Weak to Strong Learner M Møller Høgsgaard, K Green Larsen, M Ritzert arXiv e-prints, arXiv: 2301.11571, 2023		2023
Computer-Aided Fuel Design with Generative Graph Machine Learning JG Rittig, M Ritzert, AM Schweidtmann, S Winkler, JM Weber, P Morsch, ... 2022 AIChE Annual Meeting, 2022		2022

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