Sat 7:00 a.m. - 7:30 a.m.
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Pre-structured low-dimensional manifolds for rapid and efficient learning, memory, and inference in the brain
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Invited Talk
)
>
SlidesLive Video
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Ila Fiete
🔗
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Sat 7:30 a.m. - 7:40 a.m.
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Expressive dynamics models with nonlinear injective readouts enable reliable recovery of latent features from neural activity
(
Contributed Talk
)
>
SlidesLive Video
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Christopher Versteeg
🔗
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Sat 7:40 a.m. - 7:50 a.m.
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On Complex Network Dynamics of an In-Vitro Neuronal System during Rest and Gameplay
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Contributed Talk
)
>
SlidesLive Video
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Moein Khajehnejad
🔗
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Sat 7:50 a.m. - 8:00 a.m.
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Geometry of abstract learned knowledge in deep RL agents
(
Contributed Talk
)
>
link
SlidesLive Video
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James Mochizuki-Freeman
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Sat 8:00 a.m. - 8:20 a.m.
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Coffee Break
(
Coffee Break
)
>
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Sat 8:20 a.m. - 8:50 a.m.
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Topological Deep Learning: Going Beyond Graph Data
(
Invited Talk
)
>
SlidesLive Video
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Mustafa Hajij
🔗
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Sat 8:50 a.m. - 9:00 a.m.
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Spectral Maps for Learning on Subgraphs
(
Contributed Talk
)
>
SlidesLive Video
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Marco Pegoraro
🔗
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Sat 9:00 a.m. - 9:10 a.m.
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Data Augmentations in Deep Weight Spaces
(
Contributed Talk
)
>
SlidesLive Video
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Aviv Shamsian
🔗
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Sat 9:10 a.m. - 9:20 a.m.
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From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
(
Contributed Talk
)
>
SlidesLive Video
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Irene Cannistraci
🔗
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Sat 9:20 a.m. - 9:30 a.m.
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Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
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Contributed Talk
)
>
SlidesLive Video
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Pim de Haan
🔗
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Sat 9:30 a.m. - 10:00 a.m.
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The Role of World Models in Intelligence
(
Discussion Panel
)
>
SlidesLive Video
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Sat 10:00 a.m. - 11:20 a.m.
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Lunch Break
(
Lunch Break
)
>
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🔗
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Sat 11:20 a.m. - 11:50 a.m.
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From Local Diffeomorphism Detection to Symbolic Representation
(
Invited Talk
)
>
SlidesLive Video
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Doris Tsao
🔗
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Sat 11:50 a.m. - 12:20 p.m.
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Rotation-equivariant predictive modeling reveals the functional organization of primary visual cortex
(
Invited Talk
)
>
SlidesLive Video
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Alexander Ecker
🔗
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Sat 12:20 p.m. - 12:30 p.m.
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Internal Representations of Vision Models Through the Lens of Frames on Data Manifolds
(
Contributed Talk
)
>
SlidesLive Video
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Henry Kvinge
🔗
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Sat 12:30 p.m. - 1:00 p.m.
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Physics Priors in Machine Learning
(
Invited Talk
)
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SlidesLive Video
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Max Welling
🔗
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Sat 1:00 p.m. - 1:30 p.m.
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Coffee Break
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🔗
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Sat 1:30 p.m. - 1:40 p.m.
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Symmetry Breaking and Equivariant Neural Networks
(
Contributed Talk
)
>
SlidesLive Video
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Oumar Kaba
🔗
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Sat 1:40 p.m. - 1:50 p.m.
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Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks
(
Contributed Talk
)
>
SlidesLive Video
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Sho Sonoda
🔗
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Sat 1:50 p.m. - 2:00 p.m.
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Towards Information Theory-Based Discovery of Equivariances
(
Contributed Talk
)
>
SlidesLive Video
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Hippolyte Charvin
🔗
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Sat 2:00 p.m. - 2:05 p.m.
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Announcements & Closing Remarks
(
Closing remarks
)
>
SlidesLive Video
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🔗
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Sat 2:05 p.m. - 3:00 p.m.
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Poster Session
(
Poster Session
)
>
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🔗
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-
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Joint Group Invariant Functions on Data-Parameter Domain Induce Universal Neural Networks
(
Oral
)
>
link
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Sho Sonoda · Hideyuki Ishi · Isao Ishikawa · Masahiro Ikeda
🔗
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-
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Towards Information Theory-Based Discovery of Equivariances
(
Oral
)
>
link
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Hippolyte Charvin · Nicola Catenacci Volpi · Daniel Polani
🔗
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-
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Expressive dynamics models with nonlinear injective readouts enable reliable recovery of latent features from neural activity
(
Oral
)
>
link
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Christopher Versteeg · Andrew Sedler · Jonathan McCart · Chethan Pandarinath
🔗
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-
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Data Augmentations in Deep Weight Spaces
(
Oral
)
>
link
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13 presenters
Aviv Shamsian · David Zhang · Aviv Navon · Yan Zhang · Miltiadis (Miltos) Kofinas · Idan Achituve · Riccardo Valperga · Gertjan Burghouts · Efstratios Gavves · Cees Snoek · Ethan Fetaya · Gal Chechik · Haggai Maron
🔗
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-
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Internal Representations of Vision Models Through the Lens of Frames on Data Manifolds
(
Oral
)
>
link
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Henry Kvinge · Grayson Jorgenson · Davis Brown · Charles Godfrey · Tegan Emerson
🔗
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-
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Spectral Maps for Learning on Subgraphs
(
Oral
)
>
link
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Marco Pegoraro · Riccardo Marin · Arianna Rampini · Simone Melzi · Luca Cosmo · Emanuele Rodolà
🔗
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-
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Euclidean, Projective, Conformal: Choosing a Geometric Algebra for Equivariant Transformers
(
Oral
)
>
link
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Pim de Haan · Taco Cohen · Johann Brehmer
🔗
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-
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On Complex Network Dynamics of an In-Vitro Neuronal System during Rest and Gameplay
(
Oral
)
>
link
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Moein Khajehnejad · Forough Habibollahi · Alon Loeffler · Brett J. Kagan · Adeel Razi
🔗
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-
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Symmetry Breaking and Equivariant Neural Networks
(
Oral
)
>
link
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Oumar Kaba · Siamak Ravanbakhsh
🔗
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-
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From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
(
Oral
)
>
link
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Irene Cannistraci · Luca Moschella · Marco Fumero · Valentino Maiorca · Emanuele Rodolà
🔗
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-
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Learning Useful Representations of Recurrent Neural Network Weight Matrices
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Poster
)
>
link
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Vincent Herrmann · Francesco Faccio · Jürgen Schmidhuber
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-
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Distance Learner: Incorporating Manifold Prior to Model Training
(
Poster
)
>
link
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Aditya Chetan · Nipun Kwatra
🔗
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-
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An Information-Theoretic Understanding of Maximum Manifold Capacity Representations
(
Poster
)
>
link
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Victor Lecomte · Rylan Schaeffer · Berivan Isik · Mikail Khona · Yann LeCun · Sanmi Koyejo · Andrey Gromov · Ravid Shwartz-Ziv
🔗
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-
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Sample Efficient Modeling of Drag Coefficients for Satellites with Symmetry
(
Poster
)
>
link
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Neel Sortur · Linfeng Zhao · Robin Walters
🔗
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-
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AMES: A Differentiable Embedding Space Selection Framework for Latent Graph Inference
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Poster
)
>
link
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Yuan Lu · Haitz Sáez de Ocáriz Borde · Pietro Lió
🔗
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-
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Optimal packing of attractor states in neural representations
(
Poster
)
>
link
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John Vastola
🔗
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-
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Grokking in recurrent networks with attractive and oscillatory dynamics
(
Poster
)
>
link
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Keith Murray
🔗
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-
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Quantifying Lie Group Learning with Local Symmetry Error
(
Poster
)
>
link
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Vasco Portilheiro
🔗
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-
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How do language models bind entities in context?
(
Poster
)
>
link
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Jiahai Feng · Jacob Steinhardt
🔗
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-
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Improving Convergence and Generalization Using Parameter Symmetries
(
Poster
)
>
link
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Bo Zhao · Robert Gower · Robin Walters · Rose Yu
🔗
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-
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Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus
(
Poster
)
>
link
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Cody Tipton · Elizabeth Coda · Davis Brown · Alyson Bittner · Caitlin Hutten · Grayson Jorgenson · Tegan Emerson · Henry Kvinge
🔗
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-
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How Capable Can a Transformer Become? A Study on Synthetic, Interpretable Tasks
(
Poster
)
>
link
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Rahul Ramesh · Mikail Khona · Robert Dick · Hidenori Tanaka · Ekdeep S Lubana
🔗
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-
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Structure-wise Uncertainty for Curvilinear Image Segmentation
(
Poster
)
>
link
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Saumya Gupta · Xiaoling Hu · Chao Chen
🔗
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-
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On the Varied Faces of Overparameterization in Supervised and Self-Supervised Learning
(
Poster
)
>
link
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Matteo Gamba · Arna Ghosh · Kumar Krishna Agrawal · Blake Richards · Hossein Azizpour · Mårten Björkman
🔗
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-
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Geometric Epitope and Paratope Prediction
(
Poster
)
>
link
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Marco Pegoraro · Clémentine Dominé · Emanuele Rodolà · Petar Veličković · Andreea-Ioana Deac
🔗
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-
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RelWire: Metric Based Graph Rewiring
(
Poster
)
>
link
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Rishi Sonthalia · Anna Gilbert · Matthew Durham
🔗
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-
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Sheaf-based Positional Encodings for Graph Neural Networks
(
Poster
)
>
link
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Yu He · Cristian Bodnar · Pietro Lió
🔗
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-
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Structural Similarities Between Language Models and Neural Response Measurements
(
Poster
)
>
link
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Jiaang Li · Antonia Karamolegkou · Yova Kementchedjhieva · Mostafa Abdou · Sune Lehmann · Anders Søgaard
🔗
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-
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INRFormer: Neuron Permutation Equivariant Transformer on Implicit Neural Representations
(
Poster
)
>
link
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Lei Zhou · Varun Belagali · Joseph Bae · Prateek Prasanna · Dimitris Samaras
🔗
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-
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From Charts to Atlas: Merging Latent Spaces into One
(
Poster
)
>
link
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Donato Crisostomi · Irene Cannistraci · Luca Moschella · Pietro Barbiero · Marco Ciccone · Pietro Lió · Emanuele Rodolà
🔗
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-
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Growing Brains in Recurrent Neural Networks for Multiple Cognitive Tasks
(
Poster
)
>
link
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Ziming Liu · Mikail Khona · Ila Fiete · Max Tegmark
🔗
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-
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Are “Hierarchical” Visual Representations Hierarchical?
(
Poster
)
>
link
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Ethan Shen · Ali Farhadi · Aditya Kusupati
🔗
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-
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Homological Convolutional Neural Networks
(
Poster
)
>
link
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Antonio Briola · Yuanrong Wang · Silvia Bartolucci · Tomaso Aste
🔗
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-
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Visual Scene Representation with Hierarchical Equivariant Sparse Coding
(
Poster
)
>
link
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Christian A Shewmake · Domas Buracas · Hansen Lillemark · Jinho Shin · Erik Bekkers · Nina Miolane · Bruno Olshausen
🔗
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-
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Symmetry-based Learning of Radiance Fields for Rigid Objects
(
Poster
)
>
link
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Zhiwei Han · Stefan Matthes · Hao Shen · Yuanting Liu
🔗
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-
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Decorrelating neurons using persistence
(
Poster
)
>
link
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Rubén Ballester · Carles Casacuberta · Sergio Escalera
🔗
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-
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Scalar Invariant Networks with Zero Bias
(
Poster
)
>
link
|
Chuqin Geng · Xiaojie Xu · Haolin Ye · Xujie Si
🔗
|
-
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Fast Temporal Wavelet Graph Neural Networks
(
Poster
)
>
link
|
Duc Thien Nguyen · Tuan Nguyen · Truong Son Hy · Risi Kondor
🔗
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-
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Manifold-augmented Eikonal Equations: Geodesic Distances and Flows on Differentiable Manifolds.
(
Poster
)
>
link
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Daniel Kelshaw · Luca Magri
🔗
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-
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Pitfalls in Measuring Neural Transferability
(
Poster
)
>
link
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Suryaka Suresh · Vinayak Abrol · Anshul Thakur
🔗
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-
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Random Field Augmentations for Self-Supervised Representation Learning
(
Poster
)
>
link
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Philip Mansfield · Arash Afkanpour · Warren Morningstar · Karan Singhal
🔗
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-
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Changes in the geometry of hippocampal representations across brain states
(
Poster
)
>
link
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Wannan Yang · Chen Sun · Gyorgy Buzsaki
🔗
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-
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Entropy-MCMC: Sampling from Flat Basins with Ease
(
Poster
)
>
link
|
Bolian Li · Ruqi Zhang
🔗
|
-
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Roto-translation Equivariant YOLO for Aerial Images
(
Poster
)
>
link
|
Benjamin Maurel · Samy Blusseau · Santiago Velasco-Forero · Teodora Petrisor
🔗
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-
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Full-dimensional Characterisation of Time-Warped Spike-Time Stimulus-Response Distribution Geometries
(
Poster
)
>
link
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James Isbister
🔗
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-
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Emergence of Latent Binary Encoding in Deep Neural Network Classifiers
(
Poster
)
>
link
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Luigi Sbailò · Luca Ghiringhelli
🔗
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-
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Testing Assumptions Underlying a Unified Theory for the Origin of Grid Cells
(
Poster
)
>
link
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Rylan Schaeffer · Mikail Khona · Adrian Bertagnoli · Sanmi Koyejo · Ila Fiete
🔗
|
-
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SO(3)-Equivariant Representation Learning in 2D Images
(
Poster
)
>
link
|
Darnell Granberry · Alireza Nasiri · Jiayi Shou · Alex J. Noble · Tristan Bepler
🔗
|
-
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Self-Supervised Latent Symmetry Discovery via Class-Pose Decomposition
(
Poster
)
>
link
|
Gustaf Tegnér · Hedvig Kjellstrom
🔗
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-
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Discovering Latent Causes and Memory Modification: A Computational Approach Using Symmetry and Geometry
(
Poster
)
>
link
|
Arif Dönmez
🔗
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-
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On the Information Geometry of Vision Transformers
(
Poster
)
>
link
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Sonia Joseph · Kumar Krishna Agrawal · Arna Ghosh · Blake Richards
🔗
|
-
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The Variability of Representations in Mice and Humans Changes with Learning, Engagement, and Attention
(
Poster
)
>
link
|
11 presenters
Praveen Venkatesh · Corbett Bennett · Sam Gale · Juri Minxha · Hristos Courellis · Greggory Heller · Tamina Ramirez · Severine Durand · Ueli Rutishauser · Shawn Olsen · Stefan Mihalas
🔗
|
-
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Explicit Neural Surfaces: Learning Continuous Geometry with Deformation Fields
(
Poster
)
>
link
|
Thomas Walker · Octave Mariotti · Amir Vaxman · Hakan Bilen
🔗
|
-
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Symmetric Models for Radar Response Modeling
(
Poster
)
>
link
|
Colin Kohler · Nathan Vaska · Ramya Muthukrishnan · Whangbong Choi · Jung Yeon Park · Justin Goodwin · Rajmonda Caceres · Robin Walters
🔗
|
-
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The Surprising Effectiveness of Equivariant Models in Domains with Latent Symmetry
(
Poster
)
>
link
|
Dian Wang · Jung Yeon Park · Neel Sortur · Lawson Wong · Robin Walters · Robert Platt
🔗
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-
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Large language models partially converge toward human-like concept organization
(
Poster
)
>
link
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Jonathan Gabel Christiansen · Mathias Gammelgaard · Anders Søgaard
🔗
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-
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Cayley Graph Propagation
(
Poster
)
>
link
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Joseph Wilson · Petar Veličković
🔗
|
-
|
Curvature Fields from Shading Fields
(
Poster
)
>
link
|
Xinran Han · Todd Zickler
🔗
|
-
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A Comparison of Equivariant Vision Models with ImageNet Pre-training
(
Poster
)
>
link
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David Klee · Jung Yeon Park · Robert Platt · Robin Walters
🔗
|
-
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Almost Equivariance via Lie Algebra Convolutions
(
Poster
)
>
link
|
Daniel McNeela
🔗
|
-
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Deep Ridgelet Transform: Voice with Koopman Operator Constructively Proves Universality of Formal Deep Networks
(
Poster
)
>
link
|
Sho Sonoda · Yuka Hashimoto · Isao Ishikawa · Masahiro Ikeda
🔗
|
-
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Learning Symmetrization for Equivariance with Orbit Distance Minimization
(
Poster
)
>
link
|
Dat Nguyen · Jinwoo Kim · Hongseok Yang · Seunghoon Hong
🔗
|
-
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Algebraic Topological Networks via the Persistent Local Homology Sheaf
(
Poster
)
>
link
|
Gabriele Cesa · Arash Behboodi
🔗
|
-
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Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach
(
Poster
)
>
link
|
Giovanni Luca Marchetti · Gabriele Cesa · Kumar Pratik · Arash Behboodi
🔗
|
-
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Opening Remarks
(
Opening Remarks
)
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Opening Remarks
(
Opening Remarks
)
>
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