What is this?
A curated GitHub reading list of machine learning research papers: every entry pairs the paper PDF with a link to an open-source implementation and shows that implementation's star count. Nothing to install or run.
A curated GitHub reading list of machine learning research papers: every entry pairs the paper PDF with a link to an open-source implementation and shows that implementation's star count. Nothing to install or run.Is this a paper index, or does it host the code itself?Just an index. The repository is one set of markdown tables where each row is a paper title linked to its PDF, plus the conference, a code link out to a separate implementation repo, and its star count.
Just an index. The repository is one set of markdown tables where each row is a paper title linked to its PDF, plus the conference, a code link out to a separate implementation repo, and its star count.Is this list still being updated?No. The repository description states it is no longer maintained, and the last push was in January 2020, so treat it as a snapshot of roughly 2016 to 2019 research.
No. The repository description states it is no longer maintained, and the last push was in January 2020, so treat it as a snapshot of roughly 2016 to 2019 research.Who actually gets value from this list?Researchers and practitioners who want to reproduce or reuse models instead of implementing papers from scratch. The star counts let you spot which implementations the community actually trusts.
Researchers and practitioners who want to reproduce or reuse models instead of implementing papers from scratch. The star counts let you spot which implementations the community actually trusts.Which conferences does the list cover?Computer vision venues CVPR, ICCV and ECCV alongside machine learning venues ICML and NIPS; the visible table rows come mostly from 2016 to 2018 editions of those conferences.
Computer vision venues CVPR, ICCV and ECCV alongside machine learning venues ICML and NIPS; the visible table rows come mostly from 2016 to 2018 editions of those conferences.How do I find a working implementation for a paper here?Find the paper's row and follow its code link. Comparing the star counts across rows points you to the most popular, battle-tested implementation first.
Find the paper's row and follow its code link. Comparing the star counts across rows points you to the most popular, battle-tested implementation first.Why pair papers with code at all?Reproducing results from a PDF alone is slow and error-prone; a linked implementation lets you verify the paper's claims and start building on the model immediately.
Reproducing results from a PDF alone is slow and error-prone; a linked implementation lets you verify the paper's claims and start building on the model immediately.What are similar projects?figures4papers, CVPR2026-Papers-with-Code, WholebodyVLA, transferlearning, awesome-rsi, the-gan-zoo, deep_learning_object_detection, awesome-deep-learning-papers
figures4papers, CVPR2026-Papers-with-Code, WholebodyVLA, transferlearning, awesome-rsi, the-gan-zoo, deep_learning_object_detection, awesome-deep-learning-papersWhich topics is it in?cvpr, code, papers, collection, paper, reference, deprecated, computer-vision, learning, list, markdown, curated-list
cvpr, code, papers, collection, paper, reference, deprecated, computer-vision, learning, list, markdown, curated-list