[R] Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture - Meta Ai Yann LeCun et al - Code + checkpoints released!

Paper: [https://arxiv.org/abs/2301.08243](https://arxiv.org/abs/2301.08243)

**Github:** [**https://github.com/facebookresearch/ijepa**](https://github.com/facebookresearch/ijepa) **Includes code + checkpoints!**

Abstract:

>This paper demonstrates an approach for learning highly semantic image representations without relying on hand-crafted data-augmentations. We introduce the Image-based Joint-Embedding Predictive Architecture (I-JEPA), a non-generative approach for self-supervised learning from images. The idea behind I-JEPA is simple: from a single context block, predict the representations of various target blocks in the same image. A core design choice to guide I-JEPA towards producing semantic representations is the masking strategy; specifically, it …

abstract architecture context core data design embedding generative i-jepa image images jepa machinelearning paper predictive self-supervised learning semantic supervised learning