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intcomp/Sub-JEPA

Official implementation of the paper: Sub-JEPA: Subspace Gaussian Regularization for Stable End-to-End World Models.

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Python
67
2
2 contributors
Apache License 2.0
website
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How fast intcomp/Sub-JEPA is gaining stars, and where it lands on Trendshift and GitHub Trending

Activity and trending

Stars, forks and merged pull requests each day or month, lined up with the repository's rank on Trendshift Trending

Sep 3 – Oct 24, 2026

Stars +6 in 52 days

01
1

Forks +1 in 52 days

01
1

Merged PRs 0 in 52 days

01

Trendshift Trendingwhere the repository ranked each day it made the top 25

Not in the Trendshift top 25 in this period

Sep 3Sep 10Sep 17Sep 24Oct 1Oct 8Oct 15Oct 22
The left and right arrow keys step from day to day; Home and End go to the first and the last

Stars, forks, merged pull requests and Trendshift Trending rank, by day
DayStars gainedForks gainedMerged PRs
Thu, Sep 3, 2026+1+00
Fri, Sep 4, 2026+0+00
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Mon, Sep 7, 2026+0+00
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Sun, Sep 13, 2026+1+00
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Sat, Sep 26, 2026+0+10
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Mon, Sep 28, 2026+1+00
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Fri, Oct 16, 2026+1+00
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Sat, Oct 24, 2026+0+00
Total+6+10
  • 1#1 on the list
  • 7Rank that day
  • Not trending

Social mentions

Recent discussions about this repository across the web
  1. May 181 post

    • Sub-JEPA: a simple fix to LeCun group's LeWorldModel that consistently improves performance [P]

      Read full on Reddit

      r/MachineLearning

  2. May 122 posts

    • We're releasing Sub-JEPA 🌐 LeWM makes end-to-end JEPA world models stable with Gaussian regularization. Sub-JEPA asks: what if the full-space Gaussian prior is too strong? Code: #WorldModels #JEPA…

      Read full on X, posted by @DrHenryLin

      @DrHenryLin · x.com

    • Amazing work! We extend LeWM by moving the isotropic Gaussian from the full embedding space into random orthogonal subspaces — since latents lie on low-dim manifolds, this relaxes an overly strong…

      Read full on X, posted by @drkaizhao

      @drkaizhao · x.com

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