https://github.com/lucidrains/disco-rl-pytorch
Implementation and explorations into DiscoRL, Discovering state-of-the-art reinforcement learning algorithms, David Silver's last work at Deepmind
https://github.com/lucidrains/disco-rl-pytorch
artificial-intelligence deep-learning meta-learning reinforcement-learning
Last synced: about 1 month ago
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Implementation and explorations into DiscoRL, Discovering state-of-the-art reinforcement learning algorithms, David Silver's last work at Deepmind
- Host: GitHub
- URL: https://github.com/lucidrains/disco-rl-pytorch
- Owner: lucidrains
- License: mit
- Created: 2026-06-02T19:15:29.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2026-06-07T16:57:34.000Z (about 1 month ago)
- Last Synced: 2026-06-08T10:27:03.350Z (about 1 month ago)
- Topics: artificial-intelligence, deep-learning, meta-learning, reinforcement-learning
- Language: Python
- Homepage:
- Size: 486 KB
- Stars: 17
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## DiscoRL - Pytorch (wip)
Implementation and explorations into [Discovering state-of-the-art reinforcement learning algorithms](https://www.nature.com/articles/s41586-025-09761-x) (DiscoRL), David Silver's last work at Deepmind.
## Citation
```bibtex
@article{Oh2025Discovering,
author = {Oh, Junhyuk and Farquhar, Gregory and Kemaev, Iurii and Calian, Dan A. and Hessel, Matteo and Zintgraf, Luisa and Singh, Satinder and van Hasselt, Hado and Silver, David},
title = {Discovering state-of-the-art reinforcement learning algorithms},
journal = {Nature},
year = {2025},
volume = {648},
number = {8093},
pages = {312--319},
doi = {10.1038/s41586-025-09761-x}
}
```
```bibtex
@misc{tandon2025endtoendtesttimetraininglong,
title = {End-to-End Test-Time Training for Long Context},
author = {Arnuv Tandon and Karan Dalal and Xinhao Li and Daniel Koceja and Marcel Rød and Sam Buchanan and Xiaolong Wang and Jure Leskovec and Sanmi Koyejo and Tatsunori Hashimoto and Carlos Guestrin and Jed McCaleb and Yejin Choi and Yu Sun},
year = {2025},
eprint = {2512.23675},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2512.23675},
}
```