N. Piatkowski, K. Morik, N. Kriege, C. Morris, M. Fey, F. Weichert, N. Bertram, J. Ellert, J. Fischer and L. Pfahler, "Structured Data" in Machine Learning under Resource Constraints - Fundamentals, De Gruyter, 2023, pp. 99--178.

doi:10.1515/9783110785944-004

M. Fey, J. E. Lenssen, F. Weichert and J. Leskovec, "GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings" , International Conference on Machine Learning (ICML), 2021.

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M. Kleineberg, M. Fey and F. Weichert, "Adversarial Generation of Continuous Implicit Shape Representations" in Eurographics, 2020.

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M. Fey, J. E. Lenssen, C. Morris, J. Masci and N. Kriege, "Deep Graph Matching Consensus" in International Conference on Learning Representations (ICLR), 2020.

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M. Fey, J. Yuen and F. Weichert, "Hierarchical Inter-Message Passing for Learning on Molecular Graphs" in ICML Graph Representation Learning and Beyond (GRL+), 2020.

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M. Fey and J. E. Lenssen, "Fast Graph Representation Learning with PyTorch Geometric" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.

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W. Tillmann, C. Schaak, J. Zajaczkowski, H. Müller, D. Hegels, M. Gaspar, B. Kuhlenkötter and D. D. Störkle, "Investigation of a procedure for the simulation-based optimisation of robot paths for thermal spraying" , Thermal Spray Bulletin, vol. 12, pp. 89-97, 2019.

M. Fey, "Just Jump: Dynamic Neighborhood Aggregation in Graph Neural Networks" in ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.

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C. Morris, M. Ritzert, M. Fey, W. L. Hamilton, J. E. Lenssen, G. Rattan and M. Grohe, "Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks" in 33rd AAAI Conference on Artificial Intelligence (AAAI-19), 2019.

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M. Fey, J. E. Lenssen, F. Weichert and H. Müller, "SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels" in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. pp. 869-877.

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J. E. Lenssen, M. Fey and P. Libuschewski, "Group Equivariant Capsule Networks" in Neural Information Processing Systems (NIPS) 32, 2018.

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N. Kriege, M. Fey, D. Fisseler, P. Mutzel and F. Weichert, "Recognizing Cuneiform Signs Using Graph Based Methods" in International Workshop on Cost-Sensitive Learning (COST), 2018.

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W. Tillmann, C. Schaak, J. Zajaczkowski, H. Müller, D. Hegels, M. Gaspar, B. Kuhlenkötter and D. D. Störkle, "Investigation into the properties of HVOF-sprayed WC-Co coatings on plane and complex surfaces, manufactured with an evolution-based path planning method" , Thermal Spray Bulletin, vol. 11, 2018.

M. Otten and H. Müller, "Automatic Tracking of Interactive Virtual Players by Cameras Using a Voronoi Freespace Representation" , Research Report 2006, Fachbereich Informatik, Universität Dortmund, 44221 Dortmund, Germany, 2006.

X. Ren, B. Kuhlenkötter and H. Müller, "Simulation and verification of belt grinding with industrial robots" , International Journal of Machine Tools \& Manufacture, vol. 46, pp. 708-716, 2006.

X. Ren, H. Müller and B. Kuhlenkötter, "Surfel-based Surface modeling for robotic belt grinding simulation" , Journal of Zhejiang University - Science A, vol. 7(7), pp. 1215 - 1224, 2006. Zhejiang University Press, co-published with Springer-Verlag GmbH.

H. Müller and M. Otte, "Solving algebraic systems in Bernstein-Bezier repräsentation" in Computional Geometry, Lecture Notes in Computer Science, Springer-Verlag, 1991, pp. 161-169.

H. Müller, J. Winckler, S. Grzybek, M. Otte, B. Stoll, F. Equoy and N. Higelin, "The program animation system PASTIS" in The Journal of Visualization and Computer Animation 2, Springer-Verlag, 1991, pp. 26-33.