Scaling Down Deep Learning with MNIST-1D

Samuel James Greydanus; Dmitry Kobak

2024 ICML ICML 2024

Scaling Down Deep Learning with MNIST-1D

Abstract

No abstract available. No abstract was captured for this paper when its proceedings were scraped - most often an older edition published without one online. How the corpus is built.

Authors

Samuel James Greydanus, Dmitry Kobak

Topics

Machine Learning > Application Areas > Efficient Computing Deep Learning > Techniques > Model Architecture Deep Learning > Learning Types > Self-Supervised Learning

Keywords

lottery ticket deep double descent inductive biases low-compute low-memory procedurally generated

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