Paper

  • Learning the Structure of Large Networked Systems Obeying Conservation Laws

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning the Structure of Large Networked Systems Obeying Conservation Laws

    Rajasekhar Anguluri, Gautam Dasarathy, Anirudh Rayas p14637-14650 from Advances in Neural Information Processing Systems 35
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  • Learning threshold neurons via edge of stability

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning threshold neurons via edge of stability

    Kwangjun Ahn, Sebastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang p19540-19569 from Advances in Neural Information Processing Systems 36
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  • Learning Time-Invariant Representations for Individual Neurons from Population Dynamics

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning Time-Invariant Representations for Individual Neurons from Population Dynamics

    Tianxing He, Trung Le, Lu Mi, Eli Shlizerman, Uygar Sümbül p46007-46026 from Advances in Neural Information Processing Systems 36
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  • Learning to Accelerate Partial Differential Equations Via Latent Global Evolution

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Accelerate Partial Differential Equations Via Latent Global Evolution

    Jure Leskovec, Takashi Maruyama, Tailin Wu p2240-2253 from Advances in Neural Information Processing Systems 35
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  • Learning to Assist Humans without Inferring Rewards

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Assist Humans without Inferring Rewards

    Anca Dragan, Evan Ellis, Benjamin Eysenbach, Sergey Levine, Vivek Myers p71540-71567 from Advances in Neural Information Processing Systems 37
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  • Learning to Attack Federated Learning: A Model-Based Reinforcement Learning Attack Framework

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Attack Federated Learning: A Model-Based Reinforcement Learning Attack Framework

    Henger Li, Xiaolin Sun, Zizhan Zheng p35007-35020 from Advances in Neural Information Processing Systems 35
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  • Learning to Augment Distributions for Out-of-distribution Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Augment Distributions for Out-of-distribution Detection

    Zhen Fang, Bo Han, Yixuan Li, Feng Liu, Qizhou Wang, Yonggang Zhang p73274-73286 from Advances in Neural Information Processing Systems 36
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  • Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Balance Altruism and Self-interest Based on Empathy in Mixed-Motive Games

    Xue Feng, Yizhe Huang, Fanqi Kong, Siyuan Qi, Song-Chun Zhu p135819-135842 from Advances in Neural Information Processing Systems 37
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  • Learning to be Smooth: An End-to-End Differentiable Particle Smoother

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to be Smooth: An End-to-End Differentiable Particle Smoother

    Erik Sudderth, Ali Younis p7125-7155 from Advances in Neural Information Processing Systems 37
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  • Learning to Branch with Tree MDPs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Branch with Tree MDPs

    Karen Aardal, Feng Chen, Didier Chetelat, Maxime Gasse, Andrea Lodi, Lara Scavuzzo, Neil Yorke-Smith p18514-18526 from Advances in Neural Information Processing Systems 35
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  • Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Break the Loop: Analyzing and Mitigating Repetitions for Neural Text Generation

    Deng Cai, Jian Li, Huayang Li, Xiaojiang Liu, Jin Xu, Jianhao Yan p3082-3095 from Advances in Neural Information Processing Systems 35
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  • Learning to Compare Nodes in Branch and Bound with Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Compare Nodes in Branch and Bound with Graph Neural Networks

    Didier Chetelat, Abdel Ghani Labassi, Andrea Lodi p32000-32010 from Advances in Neural Information Processing Systems 35
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