Paper

  • Scaling Animal to Human Injury Response for Use in Improved Behind Armor Blunt Trauma Injury Criteria

    Royal Military Academy (Belgium)

    Scaling Animal to Human Injury Response for Use in Improved Behind Armor Blunt Trauma Injury Criteria

    J. Op’t Eynde, A. S. Shah, J. A. McMahon, D. Y. Pang, B. D. Stemper, N. Yoganandan, R. S. Salzar, B. J. McEntire, C. R. Bass p55-64 from 16th Personal Armour Systems Symposium (PASS 2023)
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  • Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Continuous Latent Variable Models as Probabilistic Integral Circuits

    Cassio de Campos, Gennaro Gala, Erik Quaeghebeur, Antonio Vergari p10959-10987 from Advances in Neural Information Processing Systems 37
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  • Scaling Data-Constrained Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Data-Constrained Language Models

    Boaz Barak, Teven Le Scao, Niklas Muennighoff, Aleksandra Piktus, Sampo Pyysalo, Colin Raffel, Alexander Rush, Nouamane Tazi, Thomas Wolf p50358-50376 from Advances in Neural Information Processing Systems 36
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  • Scaling Law for Time Series Forecasting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Law for Time Series Forecasting

    Lei Li, Huan Ma, Qinwei Ma, Jingzhe Shi p83314-83344 from Advances in Neural Information Processing Systems 37
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  • Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations

    Loubna Allal, Elie Bakouch, Alexander Hägele, Martin Jaggi, Atli Kosson, Leandro Von Werra p76232-76264 from Advances in Neural Information Processing Systems 37
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  • Scaling Laws for Hyperparameter Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Laws for Hyperparameter Optimization

    Josif Grabocka, Maciej Janowski, Arlind Kadra, Martin Wistuba p47527-47553 from Advances in Neural Information Processing Systems 36
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  • Scaling laws for language encoding models in fMRI

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling laws for language encoding models in fMRI

    Richard Antonello, Alexander Huth, Aditya Vaidya p21895-21907 from Advances in Neural Information Processing Systems 36
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  • Scaling laws for learning with real and surrogate data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling laws for learning with real and surrogate data

    Ayush Jain, Andrea Montanari, Eren Sasoglu p110246-110289 from Advances in Neural Information Processing Systems 37
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  • Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms

    Yaswanth Chittepu, Chelsea Finn, Joey Hejna, W. Knox, Scott Niekum, Ryan Park, Rafael Rafailov, Harshit Sikchi p126207-126242 from Advances in Neural Information Processing Systems 37
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  • Scaling Laws in Linear Regression: Compute, Parameters, and Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Laws in Linear Regression: Compute, Parameters, and Data

    Peter Bartlett, Sham Kakade, Jason Lee, Licong Lin, Jingfeng Wu p60556-60606 from Advances in Neural Information Processing Systems 37
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  • Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling Laws with Vocabulary: Larger Models Deserve Larger Vocabularies

    Longxu Dou, Min Lin, Qian Liu, Ping Luo, Niklas Muennighoff, Chaofan Tao, Zhongwei Wan, Ngai Wong p114147-114179 from Advances in Neural Information Processing Systems 37
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  • Scaling MLPs: A Tale of Inductive Bias

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Scaling MLPs: A Tale of Inductive Bias

    Sotiris Anagnostidis, Gregor Bachmann, Thomas Hofmann p60821-60840 from Advances in Neural Information Processing Systems 36
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