Paper

  • Shot-To-Shot Consistency of Trauma Measurements in a BABT-Rig and Roma Plastilina #1 Clay

    Royal Military Academy (Belgium)

    Shot-To-Shot Consistency of Trauma Measurements in a BABT-Rig and Roma Plastilina #1 Clay

    D. B. Rahbek, G. Roberson, T. Thorvaldsen, A. Wien p90-99 from 17th Personal Armour Systems Symposium (PASS 2025)
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  • SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    SHOT: Suppressing the Hessian along the Optimization Trajectory for Gradient-Based Meta-Learning

    Nojun Kwak, Junhoo Lee, Jayeon Yoo p61450-61465 from Advances in Neural Information Processing Systems 36
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  • Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Should I Stop or Should I Go: Early Stopping with Heterogeneous Populations

    Hammaad Adam, Lorin Crawford, Huibin Hu, Allison Koenecke, Lester Mackey, Neil Tenenholtz, Fan Yin p15799-15832 from Advances in Neural Information Processing Systems 36
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  • Should Under-parameterized Student Networks Copy or Average Teacher Weights?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Should Under-parameterized Student Networks Copy or Average Teacher Weights?

    Amire Bendjeddou, Johanni Brea, Wulfram Gerstner, Berfin Simsek p78028-78068 from Advances in Neural Information Processing Systems 36
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  • Should We Learn Most Likely Functions or Parameters?

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Should We Learn Most Likely Functions or Parameters?

    Sanyam Kapoor, Shikai Qiu, Tim G. J. Rudner, Andrew Wilson p35814-35835 from Advances in Neural Information Processing Systems 36
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  • Should We Really Edit Language Models? On the Evaluation of Edited Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Should We Really Edit Language Models? On the Evaluation of Edited Language Models

    Xiaowen Chu, Peijie Dong, Qi Li, Zeyu Li, Xiang Liu, Xinglin Pan, Zhenheng Tang p30850-30885 from Advances in Neural Information Processing Systems 37
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  • ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ShowMaker: Creating High-Fidelity 2D Human Video via Fine-Grained Diffusion Modeling

    Wenqing Chu, Errui Ding, Haocheng Feng, Zhiqiang Feng, Jiazhi Guan, Jingdong Wang, Kaisiyuan Wang, Hongtao Xie, Quanwei Yang, Lingyun Yu, Hang Zhou p51039-51062 from Advances in Neural Information Processing Systems 37
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  • ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ShuffleMixer: An Efficient ConvNet for Image Super-Resolution

    Jinshan Pan, Long Sun, Jinhui Tang p17314-17326 from Advances in Neural Information Processing Systems 35
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  • Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Shuffling Gradient-Based Methods for Nonconvex-Concave Minimax Optimization

    Lam Nguyen, Trang Tran, Quoc Tran-Dinh p55647-55666 from Advances in Neural Information Processing Systems 37
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  • Siamese Masked Autoencoders

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Siamese Masked Autoencoders

    Jia Deng, Agrim Gupta, Fei-Fei Li, Jiajun Wu p40676-40693 from Advances in Neural Information Processing Systems 36
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  • Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts

    Nhat Ho, Huy Nguyen, Alessandro Rinaldo p118357-118388 from Advances in Neural Information Processing Systems 37
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  • SIGNAL DENOISING FOR TIMBER BRIDGE STRUCTURAL HEALTH MONITORING USING OPTIMIZED VARIATIONAL MODE DECOMPOSITION

    World Conference on Timber Engineering 2025

    SIGNAL DENOISING FOR TIMBER BRIDGE STRUCTURAL HEALTH MONITORING USING OPTIMIZED VARIATIONAL MODE DECOMPOSITION

    Farshid Abdoli, Sahar Hassani, Ulrike Dackermann, Vahid Nasir, Maria Rashidi p2094-2102 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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