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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
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
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
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
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
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
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
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?
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?
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
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
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
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
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
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
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?
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
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
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
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
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
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
Proceedings of the 1st NeurIPS Workshop on Symmetry and Geometry in Neural Representations, PMLR 197:388-400
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