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Workshop
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Manifold-Constrained Nucleus-Level Denoising Diffusion Model for Structure-Based Drug Design
Shengchao Liu · Divin Yan · weitao du · Weiyang Liu · Hongyu Guo · Christian Borgs · Jennifer Chayes · Anima Anandkumar
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Poster
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Tue 4:30
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Efficient Pareto Manifold Learning with Low-Rank Structure
Weiyu CHEN · James Kwok
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Poster
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Wed 4:30
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Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds
Daniel Dodd · Louis Sharrock · Chris Nemeth
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Poster
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Wed 2:30
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Riemannian coordinate descent algorithms on matrix manifolds
Andi Han · Pratik Kumar Jawanpuria · Bamdev Mishra
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Poster
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Wed 4:30
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Manifold Integrated Gradients: Riemannian Geometry for Feature Attribution
Eslam Zaher · Maciej Trzaskowski · Quan Nguyen · Fred Roosta
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Poster
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Wed 2:30
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Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
Tingting Dan · Ziquan Wei · Won Hwa Kim · Guorong Wu
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Poster
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Tue 2:30
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First-Order Manifold Data Augmentation for Regression Learning
Ilya Kaufman · Omri Azencot
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Poster
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Thu 2:30
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Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
Jaehyeong Jo · Sung Ju Hwang
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Poster
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Wed 4:30
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Non-parametric Online Change Point Detection on Riemannian Manifolds
Xiuheng Wang · Ricardo Borsoi · Cédric Richard
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Poster
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Thu 4:30
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Optimization without Retraction on the Random Generalized Stiefel Manifold
Simon Vary · Pierre Ablin · Bin Gao · P.-A. Absil
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Poster
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Tue 4:30
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Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds
Noémie Jaquier · Leonel Rozo · Miguel González-Duque · Slava Borovitskiy · Tamim Asfour
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Poster
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Thu 4:30
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Diffusion Models Encode the Intrinsic Dimension of Data Manifolds
Jan Stanczuk · Georgios Batzolis · Teo Deveney · Carola-Bibiane Schönlieb
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