Preface to Geometry-grounded Representation Learning and Generative Modeling (GRaM) Workshop

Sharvaree Vadgama, Erik Bekkers, Alison Pouplin, Sekou-Oumar Kaba, Robin Walters, Hannah Lawrence, Tegan Emerson, Henry Kvinge, Jakub Tomczak, Stephanie Jegelka; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:1-6

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SE(3)-Hyena Operator for Scalable Equivariant Learning

Artem Moskalev, Mangal Prakash, Rui Liao, Tommaso Mansi; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:7-19

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Topology-Informed Graph Transformer

Yun Young Choi, Sun Woo Park, Minho Lee, Youngho Woo; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:20-34

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Alignment of MPNNs and Graph Transformers

Bao Nguyen, Anjana Yodaiken, Petar Veličković; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:35-49

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Stability Analysis of Equivariant Convolutional Representations Through The Lens of Equivariant Multi-layered CKNs

Soutrik Roy Chowdhury; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:50-64

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Asynchrony Invariance Loss Functions for Graph Neural Networks

Pablo Monteagudo-Lago, Arielle Rosinski, Andrew Joseph Dudzik, Petar Veličković; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:65-77

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A Coding-Theoretic Analysis of Hyperspherical Prototypical Learning Geometry

Martin Lindström, Borja Rodríguez-Gálvez, Ragnar Thobaben, Mikael Skoglund; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:78-91

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3D Shape Completion with Test-Time Training

Michael Schopf-Kuester, Zorah Lähner, Michael Moeller; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:92-102

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Commute-Time-Optimised Graphs for GNNs

Igor Sterner, Shiye Su, Petar Veličković; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:103-112

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Self-supervised detection of perfect and partial input-dependent symmetries

Alonso Urbano, David W. Romero; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:113-131

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Metric Learning for Clifford Group Equivariant Neural Networks

Riccardo Ali, Paulina Kulytė, Haitz Sáez de Ocáriz Borde, Pietro Lio; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:132-145

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Dirac–Bianconi Graph Neural Networks – Enabling Non-Diffusive Long-Range Graph Predictions

Christian Nauck, Rohan Gorantla, Michael Lindne, Konstantin Schurholt, Antonia S. J. S. Mey, Frank Hellmann; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:146-157

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Leveraging Topological Guidance for Improved Knowledge Distillation

Eun Som Jeon, Rahul Khurana, Aishani Pathak, Pavan Turaga; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:158-172

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E(n) Equivariant Message Passing Cellular Networks

Veljko Kovac̆, Erik Bekkers, Pietro Lió, Floor Eijkelboom; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:173-186

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A Simple and Expressive Graph Neural Network Based Method for Structural Link Representation

Veronica Lachi, Francesco Ferrini, Antonio Longa, Bruno Lepri, Andrea Passerini; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:187-201

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Invertible Temper Modeling using Normalizing Flows and the Effects of Structure Preserving Loss

Sylvia Howland, Keerti-Sahithi Kappagantula, Henry Kvinge, Tegan Emerson; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:202-211

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Topological and Dynamical Representations for Radio Frequency Signal Classification

Audum Meyers, Timothy Doster, Colin Olson, Tegan Emerson; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:212-221

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SCENE-Net V2: Interpretable Multiclass 3D Scene Understanding with Geometric Priors

Diogo Lavado, Cláudia Soares, Alessandra Micheletti; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:222-232

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Variational Inference Failures Under Model Symmetries: Permutation Invariant Posteriors for Bayesian Neural Networks

Yoav Gelberg, Tycho F. A. van der Ouderaa, Mark van der Wilk, Yarin Gal; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:233-248

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Joint Diffusion Processes as an Inductive Bias in Sheaf Neural Networks

Ferran Hernandez Caralt, Guillermo Bernárdez Gil, Iulia Duta, Pietro Liò, Eduard Alarcón Cot; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:249-263

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Sheaf Diffusion Goes Nonlinear: Enhancing GNNs with Adaptive Sheaf Laplacians

Olga Zaghen, Antonio Longa, Steve Azzolin, Lev Telyatnikov, Andrea Passerini, Pietro Liò; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:264-276

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Decoder ensembling for learned latent geometries

Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:277-285

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The NGT200 Dataset: Geometric Multi-View Isolated Sign Recognition

Oline Ranum, David R. Wessels, Gomer Otterspeer, Erik J. Bekkers, Floris Roelofsen, Jari I. Andersen; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:286-302

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On Fairly Comparing Group Equivariant Networks

Lucas Roos, Steve Kroon; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:303-317

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Graph Convolutional Networks for Learning Laplace-Beltrami Operators

Yingying Wu, Roger Fu, Yang Peng, Qifeng Chen; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:318-331

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The Geometry of Diffusion Models: Tubular Neighbourhoods and Singularities

Kotaro Sakamoto, Ryosuke Sakamoto, Masato Tanabe, Masatomo Akagawa, Yusuke Hayashi, Manato Yaguchi, Masahiro Suzuki, Yutaka Matsuo; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:332-363

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Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud Classification

Abihith Kothapalli, Ashkan Shahbazi, Xinran Liu, Robert Sheng, Soheil Kolouri; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:364-380

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Strongly Isomorphic Neural Optimal Transport Across Incomparable Spaces

Athina Sotiropoulou, David Alvarez-Melis; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:381-393

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Adaptive Sampling for Continuous Group Equivariant Neural Networks

Berfin Inal, Gabriele Cesa; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:394-419

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ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain

Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree Vadgama, Erik Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous̆ Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac̆, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Mez̆nar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frederic Wantiez, Alexander Weers, Patrik Zajec, Blaz̆ S̆krlj, Nina Miolane; Proceedings of the Geometry-grounded Representation Learning and Generative Modeling Workshop (GRaM), PMLR 251:420-428

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