Preface of Geometry, Topology, and Machine Learning 2025

Michael Bleher, Freya Jensen, Levin Maier, Diaaeldin Taha, Anna Wienhard; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:i-vii

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Understanding Learning Invariance in Deep Linear Networks

Hao Duan, Guido Montúfar; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:1-45

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Complete and Efficient Covariants for 3D Point Configurations

Hartmut Maennel; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:46-68

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Mathematical Foundations of Modeling ETL Process Chains

Levin Maier, Lucas Schulze, Robert Lilow, Lukas Hahn, Niko Krasowski, Arnulf Barth, Sebastian Gaebel, Ferdi Gueran, Giovanni Wagner, Falk Borgmann, Oleg Arenz, Jan Peters; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:69-78

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Classification of Histopathology Slides with Persistent Homology Convolutions

Shrunal Pothagoni, Benjamin Schweinhart; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:79-108

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Have Graph — Will Lift? The Case for Higher-Order Benchmarks

Bastian Rieck; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:109-119

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Zigzag Persistence of Large Language Models Representations

Yuri Gardinazzi, Karthik Viswanathan, Giada Panerai, Alessio Ansuini, Alberto Cazzaniga, Matteo Biagetti; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:120-129

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Zigzag Persistence of Neural Responses to Time-Varying Stimuli

Yuri Gardinazzi, Alessio Ansuini, Eugenio Piasini, Fabio Anselmi, Matteo Biagetti; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:130-144

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On a Geometry of Interbrain Networks

Nicolás Hinrichs, Noah Guzmán, Melanie Weber; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:145-152

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Mirror, Mirror of the Flow: How Does Regularization Shape Implicit Bias?

Tom Jacobs, Chao Zhou, Rebekka Burkholz; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:153-192

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In search of topological summaries for multispecies spatial patterns

Maria Jose Jimenez; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:193-200

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A Comparative Empirical Study of Relative Embedding Alignment in Neural Dynamical System Forecasters

Deniz Kucukahmetler, Maximilian Jean Hemmann, Julian Mosig von Aehrenfeld, Maximilian Amthor, Christian Deubel, Nico Scherf, Diaaeldin Taha; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:201-214

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The Geometry of Nonlinear Reinforcement Learning

Nikola Milosevic, Nico Scherf; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:215-239

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Unifying transformers and convolutional networks as equivariant maps

Elias Nyholm; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:240-245

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Manifolds with Non-Smooth Boundaries and Asymptotics of the Graph Laplacian

Susovan Pal, David Tewodrose; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:246-250

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Persistence Spheres: Bi-Continuous Linear Representations of Persistence Diagrams. Some Early Stage Results.

Matteo Pegoraro; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:251-261

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The embedded homology of hypergraphs on manifolds and configuration spaces

Shiquan Ren; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:262-268

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Computational Experiments on Random Chromatic Persistent Homology

Sophie Rosenmeier, Ondřej Draganov, Morteza Saghafian, Sebastiano Cultrera di Montesano, Herbert Edelsbrunner; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:269-276

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GNNs Getting ComFy: Community and Feature Similarity Guided Rewiring

Celia Rubio-Madrigal, Adarsh Jamadandi, Rebekka Burkholz; Proceedings of the Geometry, Topology, and Machine Learning Workshop, PMLR 325:277-318

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