Dynamically Typed

Naturally Occurring Equivariance in Neural Networks

DT #55 — December 20, 2020

Chris Olah et al. have a cool new Distill article in the Circuits thread: Naturally Occurring Equivariance in Neural Networks. “We sometimes think of understanding neural nets as being like reverse engineering a regular computer program. In this analogy, equivariance is like finding the same inlined function repeated throughout the code.”

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Recent models, datasets, and tools for machine learning research.

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