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.

Data and Resources

Cite this as

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

DOI retrieved: December 2, 2024

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