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M. Scholkemper and M. T. Schaub, "Local, Global And Scale-Dependent Node Roles," 2021 IEEE International Conference on Autonomous Systems (ICAS), Montreal, QC, Canada, 2021, pp. 1-5, doi: 10.1109/ICAS49788.2021.9551110.
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F. Frantzen, J.-B. Seby and M. T. Schaub, "Outlier Detection for Trajectories via Flow-embeddings," 2021 55th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 2021, pp. 1568-1572, doi: 10.1109/IEEECONF53345.2021.9723128.
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M. Scholkemper and M. T. Schaub, "Blind Extraction of Equitable Partitions from Graph Signals," ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Singapore, Singapore, 2022, pp. 5832-5836, doi: 10.1109/ICASSP43922.2022.9746676.
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"Improving the visibility of minorities through network growth interventions", Communication Physics 6, 108 (2023), doi:10.1038/s42005-023-01218-9
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Javier Esparza, Vincent P. Grande: "Black-Box Testing Liveness Properties of Partially Observable Stochastic Systems", ICALP 2023. 50th EATS International Colloquium on Automata, Languages and Programming, 2023
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Stamm FI, Scholkemper M, Strohmaier M, Schaub MT. Neighborhood structure configuration models. InProceedings of the ACM Web Conference 2023 2023 Apr 30 (pp. 210-220).
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"Non-isotropic Persistent Homology: Leveraging the Metric Dependency of PH", Vincent P. Grande and Michael T. Schaub, Proceedings of the 2nd Annual Learning on Graphs Conference.
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"Topological Point Cloud Clustering", Vincent P. Grande and Michael T. Schaub, 40th International Conference on Machine Learning 2023.
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Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equal, Vincent P. Grande and Michael T. Schaub, International Conference on Acoustics, Speech, and Signal Processing 2024. https://arxiv.org/abs/2311.14427
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Code for "Topological Trajectory Classification and Landmark Inference on Simplicial Complexes", Vincent P. Grande, Josef Hoppe, Florian Frantzen, Michael T. Schaub, 2024 Asilomar Conference on Signals, Systems, and Computers, IEEE.
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"A Wasserstein Graph Distance Based on Distributions of Probabilistic Node Embeddings", Scholkemper, M., Kühn, D., Nabbefeld, G., Musall, S., Kampa, B., & Schaub, M. T. (2024)
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Docker configuration for Jupyter Notebooks using IfcOpenShell for the class "2D3D"
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