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Effects of sparsity and superposition on loss in simple autoencoders

arXiv cs.LG ↗ · 2026-06-18 Cached

This paper provides a mathematical analysis of superposition in neural networks, deriving upper and lower bounds on L2 reconstruction loss for simple autoencoders with power activation functions, corroborating empirical findings by Elhage et al.

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