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Proceedings of Machine Learning Research

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Proceedings of Machine Learning Research
PMLR · 2026-06-02 · via Proceedings of Machine Learning Research

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Volume 197: NeurIPS Workshop on Symmetry and Geometry in Neural Representations, 03 December 2022, New Orleans, Lousiana, USA

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Editors: Sophia Sanborn, Christian Shewmake, Simone Azeglio, Arianna Di Bernardo, Nina Miolane

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Preface

; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:i-vi

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Computing representations for Lie algebraic networks

Noah Shutty, Casimir Wierzynski; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:1-21

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Disentangling images with Lie group transformations and sparse coding

Ho Yin Chau, Frank Qiu, Yubei Chen, Bruno Olshausen; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:22-47

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Sparse Convolutions on Lie Groups

Tycho F. A. van der Ouderaa, Mark van der Wilk; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:48-62

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Image to Icosahedral Projection for SO(3) Object Reasoning from Single-View Images

David Klee, Ondrej Biza, Robert Platt, Robin Walters; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:64-80

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Moving frame net: SE(3)-equivariant network for volumes

Mateus Sangalli, Samy Blusseau, Santiago Velasco-Forero, Jesús Angulo; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:81-97

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Periodic signal recovery with regularized sine neural networks

David A. R. Robin, Kevin Scaman, Marc Lelarge; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:98-110

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Does Geometric Structure in Convolutional Filter Space Provide Filter Redundancy Information?

Anshul Thakur, Vinayak Abrol, Pulkit Sharma; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:111-121

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Do neural networks trained with topological features learn different internal representations?

Sarah McGuire, Shane Jackson, Tegan Emerson, Henry Kvinge; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:122-136

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Fuzzy c-means clustering in persistence diagram space for deep learning model selection

Thomas Davies, Jack Aspinall, Bryan Wilder, Tran-Thanh Long; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:137-157

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On the ambiguity in classification

Arif Dönmez; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:158-170

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Connectedness of loss landscapes via the lens of Morse theory

Danil Akhtiamov, Matt Thomson; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:171-181

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Group invariant machine learning by fundamental domain projections

Benjamin Aslan, Daniel Platt, David Sheard; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:181-218

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Mixed-membership community detection via line graph curvature

Yu Tian, Zachary Lubberts, Melanie Weber; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:219-233

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Capturing cross-session neural population variability through self-supervised identification of consistent neuron ensembles

Justin Jude, Matthew G Perich, Lee E Miller, Matthias H Hennig; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:234-257

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Is the information geometry of probabilistic population codes learnable?

John J. Vastola, Zach Cohen, Jan Drugowitsch; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:258-277

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On the level sets and invariance of neural tuning landscapes

Binxu Wang, Carlos R. Ponce; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:278-300

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Learning invariance manifolds of visual sensory neurons

Luca Baroni, Mohammad Bashiri, Konstantin F. Willeke, Ján Antolík, Fabian H. Sinz; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:301-326

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Geometry of inter-areal interactions in mouse visual cortex

Ramakrishnan Iyer, Joshua Siegle, Gayathri Mahalingam, Shawn Olsen, Stefan Mihalas; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:327-353

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Topological ensemble detection with differentiable yoking

David Klindt, Sigurd Gaukstad, Melvin Vaupel, Erik Hermansen, Benjamin Dunn; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:354-369

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Conformal Isometry of Lie Group Representation in Recurrent Network of Grid Cells

Dehong Xu, Ruiqi Gao, Wen-Hao Zhang, Xue-Xin Wei, Ying Nian Wu; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:370-387

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See and Copy: Generation of complex compositional movements from modular and geometric RNN representations

Sunny Duan, Mikail Khona, Adrian Bertagnoli, Sarthak Chandra, Ila R. Fiete; Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:388-400

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