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Poster
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Neural Characteristic Activation Analysis and Geometric Parameterization for ReLU Networks
Wenlin Chen · Hong Ge
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Competition
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Sat 13:50
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#1st Place- MMGP: a Mesh Morphing Gaussian Process-based machine learning method for regression of physical problems under non-parameterized geometrical variability
Fabien Casenave
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Poster
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Fri 16:30
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Geometric Analysis of Nonlinear Manifold Clustering
Nimita Shinde · Tianjiao Ding · Daniel Robinson · Rene Vidal
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Workshop
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Sun 15:30
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Contributed talk: The State of Julia for Scientific Machine Learning
Edward Berman
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Workshop
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BiEquiFormer: Bi-Equivariant Representations for Global Point Cloud Registration
Stefanos Pertigkiozoglou · Evangelos Chatzipantazis · Kostas Daniilidis
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Workshop
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Knowledge Distillation for Teaching Symmetry Invariances
Patrick Odagiu · Nicole Nobili · Fabian Dionys Schrag · Yves Bicker · Yuhui Ding
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Workshop
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Convergence of Manifold Filter-Combine Networks
David R Johnson · Joyce Chew · Siddharth Viswanath · Edward De Brouwer · Deanna Needell · Smita Krishnaswamy · Michael Perlmutter
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Workshop
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Gradient of Clifford Neural Networks
Takashi Maruyama · Francesco Alesiani
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Workshop
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Geometric Deep Learning with Quasiconformal Neural Networks: An Introduction
Nico Alvarado · Hans Lobel
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Poster
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Thu 16:30
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Empowering Active Learning for 3D Molecular Graphs with Geometric Graph Isomorphism
Ronast Subedi · Lu Wei · Wenhan Gao · Shayok Chakraborty · Yi Liu
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Workshop
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Does equivariance matter at scale?
Johann Brehmer · Sönke Behrends · Pim de Haan · Taco Cohen
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Workshop
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The State of Julia for Scientific Machine Learning
Edward Berman · Jacob Ginesin
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