Explorations into JEPA
Project description
x-jepa
Explorations into some of the approaches advocated by Yann LeCun, and just a more wholistic architecture (JEPA) in general
Citations
@inproceedings{LeCun2022APT,
title = {A Path Towards Autonomous Machine Intelligence},
author = {Yann LeCun and Courant},
year = {2022},
url = {https://api.semanticscholar.org/CorpusID:251881108}
}
@misc{maes2026leworldmodelstableendtoendjointembedding,
title = {LeWorldModel: Stable End-to-End Joint-Embedding Predictive Architecture from Pixels},
author = {Lucas Maes and Quentin Le Lidec and Damien Scieur and Yann LeCun and Randall Balestriero},
year = {2026},
eprint = {2603.19312},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2603.19312},
}
@misc{teoh2026nextlatentpredictiontransformerslearn,
title = {Next-Latent Prediction Transformers Learn Compact World Models},
author = {Jayden Teoh and Manan Tomar and Kwangjun Ahn and Edward S. Hu and Tim Pearce and Pratyusha Sharma and Akshay Krishnamurthy and Riashat Islam and Alex Lamb and John Langford},
year = {2026},
eprint = {2511.05963},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2511.05963},
}
@inproceedings{saravanos2026learningtooptimize,
title = {Learning-to-Optimize via Deep Unfolded Flows},
author = {Augustinos D Saravanos and Oswin So and H M Sabbir Ahmad and Chuchu Fan},
booktitle = {Forty-third International Conference on Machine Learning},
year = {2026},
url = {https://openreview.net/forum?id=ZOtOq7hxJP}
}
@misc{farebrother2026compositionalplanningjumpyworld,
title = {Compositional Planning with Jumpy World Models},
author = {Jesse Farebrother and Matteo Pirotta and Andrea Tirinzoni and Marc G. Bellemare and Alessandro Lazaric and Ahmed Touati},
year = {2026},
eprint = {2602.19634},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2602.19634},
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
x_jepa-0.0.16.tar.gz
(4.7 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file x_jepa-0.0.16.tar.gz.
File metadata
- Download URL: x_jepa-0.0.16.tar.gz
- Upload date:
- Size: 4.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
37326f5b72d4ee9f7289330a23576c578590af24624760eb496c35329b65c91c
|
|
| MD5 |
452966be5e3f521c04bfcc4b7e141604
|
|
| BLAKE2b-256 |
88d29c1d908f250bd424bb83ae437ad7d005d86c765e7e7879349ec1f93d704a
|
File details
Details for the file x_jepa-0.0.16-py3-none-any.whl.
File metadata
- Download URL: x_jepa-0.0.16-py3-none-any.whl
- Upload date:
- Size: 3.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: uv/0.8.17
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
0033b3dfa9214a73e1a2f1261cbced51bcf0d9ba0195ebe8018fd80b911c2206
|
|
| MD5 |
63efce429fcc57cb3a942caeea0c193d
|
|
| BLAKE2b-256 |
c91cc4395b21a8e1f1b6ea3388f4c56aaad892ff4826bddea45b2f03c07e6577
|