Paper

  • Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convergent Bregman Plug-and-Play Image Restoration for Poisson Inverse Problems

    Samuel Hurault, Ulugbek Kamilov, Arthur Leclaire, Nicolas Papadakis p27251-27280 from Advances in Neural Information Processing Systems 36
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  • Convergent Representations of Computer Programs in Human and Artificial Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convergent Representations of Computer Programs in Human and Artificial Neural Networks

    Shashank Srikant, Ben Lipkin, Anna Ivanova, Evelina Fedorenko, Una-May O'Reilly p18834-18849 from Advances in Neural Information Processing Systems 35
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  • Convex and Non-convex Optimization Under Generalized Smoothness

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convex and Non-convex Optimization Under Generalized Smoothness

    Haochuan Li, Jian Qian, Yi Tian, Alexander Rakhlin, Ali Jadbabaie p40238-40271 from Advances in Neural Information Processing Systems 36
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  • Convex-Concave Zero-Sum Markov Stackelberg Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convex-Concave Zero-Sum Markov Stackelberg Games

    Denizalp Goktas, Arjun Prakash, Amy Greenwald p66818-66832 from Advances in Neural Information Processing Systems 36
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  • Convexity Certificates from Hessians

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convexity Certificates from Hessians

    Julien Klaus, Niklas Merk, Konstantin Wiedom, Sören Laue, Joachim Giesen p6941-6953 from Advances in Neural Information Processing Systems 35
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  • Convolution Monge Mapping Normalization for learning on sleep data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolution Monge Mapping Normalization for learning on sleep data

    Théo Gnassounou, Rémi Flamary, Alexandre Gramfort p10457-10476 from Advances in Neural Information Processing Systems 36
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  • Convolutional Differentiable Logic Gate Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutional Differentiable Logic Gate Networks

    Felix Petersen, Hilde Kuehne, Christian Borgelt, Julian Welzel, Stefano Ermon p121185-121203 from Advances in Neural Information Processing Systems 37
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  • Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited

    Mingguo He, Zhewei Wei, Ji-Rong Wen p7264-7276 from Advances in Neural Information Processing Systems 35
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  • Convolutional Neural Operators for robust and accurate learning of PDEs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutional Neural Operators for robust and accurate learning of PDEs

    Bogdan Raonic, Roberto Molinaro, Tim De Ryck, Tobias Rohner, Francesca Bartolucci, Rima Alaifari, Siddhartha Mishra, Emmanuel De Bézenac p77187-77200 from Advances in Neural Information Processing Systems 36
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  • Convolutional State Space Models for Long-Range Spatiotemporal Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutional State Space Models for Long-Range Spatiotemporal Modeling

    Jimmy Smith, Shalini De Mello, Jan Kautz, Scott Linderman, Wonmin Byeon p80690-80729 from Advances in Neural Information Processing Systems 36
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  • Convolutional Visual Prompt for Robust Visual Perception

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutional Visual Prompt for Robust Visual Perception

    Yun-Yun Tsai, Chengzhi Mao, Junfeng Yang p27897-27921 from Advances in Neural Information Processing Systems 36
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  • Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Convolutions and More as Einsum: A Tensor Network Perspective with Advances for Second-Order Methods

    Felix Dangel p96671-96727 from Advances in Neural Information Processing Systems 37
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