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Broken Neural Scaling Laws

A smoothly broken power law functional form that accurately models and extrapolates the scaling behaviors of deep neural networks for various architectures and tasks.

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Cite this as

Ethan Caballero, Kshitij Gupta, Irina Rish, David Krueger (2024). Dataset: Broken Neural Scaling Laws. https://doi.org/10.57702/vmz9zwm4

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Additional Info

Field	Value
Created	December 2, 2024
Last update	December 2, 2024
Defined In	https://doi.org/10.48550/arXiv.2210.14891
Author	Ethan Caballero
More Authors	Kshitij Gupta Irina Rish David Krueger