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Neel Nanda – GitHub Profile (neelnanda-io)

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Good quality. Reputable source with community review or editorial standards, but less rigorous than peer-reviewed venues.

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GitHub profile of Neel Nanda, a leading mechanistic interpretability researcher at Google DeepMind, whose open-source tools and research code are widely used in the AI safety and interpretability community.

Metadata

Importance: 62/100homepage

Summary

This is the GitHub profile of Neel Nanda, a prominent mechanistic interpretability researcher at Google DeepMind. His repositories include foundational tools and research code for interpretability work, including sparse autoencoders, crosscoders, and grokking analysis. His open-source contributions are widely used by the mechanistic interpretability research community.

Key Points

  • Neel Nanda is a mechanistic interpretability researcher at Google DeepMind, formerly at Anthropic.
  • Key repositories include 1L-Sparse-Autoencoder, Crosscoders, and a Mechanistic Interpretability Analysis of Grokking.
  • Hosts Neuroscope codebase for visualizing max-activating dataset examples for language model neurons.
  • Provides utility libraries like neel-plotly for interpretability research workflows compatible with PyTorch.
  • Profile serves as a central hub for open-source mechanistic interpretability tools and research code.

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 Mechanistic interpretability researcher at Google DeepMind. Formerly at Anthropic, formerly independent 

 
 
 
 
 
 
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 Report abuse 
 
 
 
 
 
 

 

 
 
 
 

 
 
 
 
 
 
 
 More 
 
 
 
 
 
 Overview 
 

 
 Repositories 
 

 
 Projects 
 

 
 Packages 
 

 
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 Popular repositories
 
 
 
 
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 1L-Sparse-Autoencoder
 1L-Sparse-Autoencoder 
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 Python 
 

 
 
 
 
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 15
 
 

 
 
 

 
 
 
 
 
 Crosscoders
 Crosscoders 
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 Python 
 

 
 
 
 
 59
 
 
 
 
 
 1
 
 

 
 
 

 
 
 
 
 
 Grokking
 Grokking 
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 A Mechanistic Interpretability Analysis of Grokking
 

 
 
 
 Python 
 

 
 
 
 
 27
 
 
 
 
 
 3
 
 

 
 
 

 
 
 
 
 
 neel-plotly
 neel-plotly 
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 A very hacky set of functions for getting plotly to do what I want when doing mech interp research, designed to be compatible with PyTorch
 

 
 
 
 Python 
 

 
 
 
 
 13
 
 
 
 
 
 4
 
 

 
 
 

 
 
 
 
 
 Neuroscope
 Neuroscope 
 Public 
 
 

 
 Accompanying codebase for neuroscope.io, a website for displaying max activating dataset examples for language model neurons
 

 
 
 
 Python 
 

 
 
 
 
 13
 
 
 
 
 
 5
 
 

 
 
 

 
 
 
 
 
 Stable-Diffusion-Interp
 Stable-Diffusion-Interp 
 Public 
 
 

 
 
 

 
 
 
 Python 
 

 
 
 
 
 9
 
 

 
 
 

 

 

 

 
 
 
 
 
 
 
 
 
 
 
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