Online Representation Learning on the Open Web
- This repository was created by Ellis Brown and contains the full source code to produce my master's thesis document.
- The thesis defense can be viewed on YouTube. Slides are available here.
Publications behind this thesis
Some of the content here is behind these publications:
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Internet Explorer: Targeted Representation Learning on the Open Web Alexander C. Li*, Ellis Brown*, Alexei A. Efros, Deepak Pathak [1] [web] [arXiv] [pdf] [code] |
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Your Diffusion Model is Secretly a Zero-Shot Classifier Alexander C. Li, Mihir Prabhudesai, Shivam Duggal, Ellis Brown, and Deepak Pathak [2] [web] [arXiv] [pdf] [code] |
The experimental source code and libraries produced for this thesis are freely available as open source software and are available in the following repository.
- internet-explorer-ssl/internet-explorer — Internet Explorer explores the web in a self-supervised manner to progressively find relevant examples that improve performance on a desired target dataset.
- ellisbrown/google-images-download — Download images from Google Images.
- ellisbrown/IN100 — Code to generate an ImageNet-100 subset using symlinks to an existing ImageNet installation.
- This repository started from Brandon Amos's great thesis repo, which was based on Cyrus Omar's thesis code, which, in turn, was based on a CMU thesis template by David Koes and others before.
The BibTeX for this document is:
@mastersthesis{brown2023online,
author = {Ellis Brown},
title = {Online Representation Learning on the Open Web},
school = {Carnegie Mellon University},
year = 2023,
month = May,
}