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Michael T. Schaub

Department of Computer Science, RWTH Aachen University, Germany

Node-Level Topological Representation Learning on Point Clouds

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Jun 04, 2024
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Graph Neural Networks Do Not Always Oversmooth

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Jun 04, 2024
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Learning From Simplicial Data Based on Random Walks and 1D Convolutions

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Apr 04, 2024
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Position Paper: Challenges and Opportunities in Topological Deep Learning

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Feb 14, 2024
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TopoX: A Suite of Python Packages for Machine Learning on Topological Domains

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Feb 07, 2024
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Combinatorial Complexes: Bridging the Gap Between Cell Complexes and Hypergraphs

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Dec 15, 2023
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Disentangling the Spectral Properties of the Hodge Laplacian: Not All Small Eigenvalues Are Equal

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Nov 24, 2023
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Non-isotropic Persistent Homology: Leveraging the Metric Dependency of PH

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Oct 25, 2023
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ICML 2023 Topological Deep Learning Challenge : Design and Results

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Oct 02, 2023
Figure 1 for ICML 2023 Topological Deep Learning Challenge : Design and Results
Figure 2 for ICML 2023 Topological Deep Learning Challenge : Design and Results
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Representing Edge Flows on Graphs via Sparse Cell Complexes

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Sep 15, 2023
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