Paper

  • A General Framework for Auditing Differentially Private Machine Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Framework for Auditing Differentially Private Machine Learning

    Francis Ferraro, Maya Fuchs, Tyler Leblond, Fred Lu, Joseph Munoz, Edward Raff, Brian Testa, Elliott Zaresky-Williams p4165-4176 from Advances in Neural Information Processing Systems 35
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  • A General Framework for Equivariant Neural Networks on Reductive Lie Groups

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Framework for Equivariant Neural Networks on Reductive Lie Groups

    Ilyes Batatia, Mario Geiger, Jose Munoz, Christoph Ortner, Lior Silberman, Tess Smidt p55260-55284 from Advances in Neural Information Processing Systems 36
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  • A General Framework for Robust G-Invariance in G-Equivariant Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Framework for Robust G-Invariance in G-Equivariant Networks

    Nina Miolane, Sophia Sanborn p67103-67124 from Advances in Neural Information Processing Systems 36
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  • A General Protocol to Probe Large Vision Models for 3D Physical Understanding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Protocol to Probe Large Vision Models for 3D Physical Understanding

    Weidi Xie, Guanqi Zhan, Chuanxia Zheng, Andrew Zisserman p43468-43498 from Advances in Neural Information Processing Systems 37
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  • A General Theory of Correct, Incorrect, and Extrinsic Equivariance

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A General Theory of Correct, Incorrect, and Extrinsic Equivariance

    Mingxi Jia, Jung Yeon Park, Robert Platt, Guanang Su, Robin Walters, Dian Wang, Xupeng Zhu p40006-40029 from Advances in Neural Information Processing Systems 36
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  • A generalized neural tangent kernel for surrogate gradient learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A generalized neural tangent kernel for surrogate gradient learning

    Luke Eilers, Sven Goedeke, Raoul-Martin Memmesheimer p9026-9085 from Advances in Neural Information Processing Systems 37
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  • A Generative Model of Symmetry Transformations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Generative Model of Symmetry Transformations

    James Allingham, Javier Antorán, José Hernández-Lobato, David Krueger, Bruno Mlodozeniec, Eric Nalisnick, Shreyas Padhy, Richard Turner p91091-91130 from Advances in Neural Information Processing Systems 37
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  • A generative model of the hippocampal formation trained with theta driven local learning rules

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A generative model of the hippocampal formation trained with theta driven local learning rules

    Caswell Barry, Claudia Clopath, Tomoki Fukai, Tom M George, Kimberly Stachenfeld p1644-1658 from Advances in Neural Information Processing Systems 36
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  • A Geometric Perspective on Variational Autoencoders

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Geometric Perspective on Variational Autoencoders

    Stephanie Allassonniere, Clément Chadebec p19618-19630 from Advances in Neural Information Processing Systems 35
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  • A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models

    Jesse Cresswell, Rasa Hosseinzadeh, Hamidreza Kamkari, Gabriel Loaiza-Ganem, Brendan Ross p38307-38354 from Advances in Neural Information Processing Systems 37
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  • A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Global Depth-Range-Free Multi-View Stereo Transformer Network with Pose Embedding

    Hujun Bao, Weikang Bian, Zhaopeng Cui, Yitong Dong, Zhaoyang Huang, Hongsheng Li, Yijin Li, Jingbo Liu, Guofeng Zhang p64773-64793 from Advances in Neural Information Processing Systems 37
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  • A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    A Globally Optimal Portfolio for m-Sparse Sharpe Ratio Maximization

    Zhao-Rong Lai, Cheng Li, Yizun Lin p17133-17160 from Advances in Neural Information Processing Systems 37
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