
# Community

learn2learn is built by a small but active community — this page acknowledges the institutions enabling those contributors and their work.

For individual contributions, please refer to our [Changelog](/changelog/).

## Universities 

<img src="/assets/img/community/usc.png" alt="USC" height="70px" /> &nbsp; &nbsp;
<img src="/assets/img/community/uiuc.png" alt="UIUC" height="70px" /> &nbsp; &nbsp;

## Companies

<img src="/assets/img/community/amazon_science.png" alt="Amazon Science" height="70px" /> &nbsp; &nbsp;
<img src="/assets/img/community/pytorch_lightning.png" alt="Pytorch Lightning" height="70px" /> &nbsp; &nbsp;

## Publications

A non-exhaustive list of papers built on top of learn2learn.
Ping [Séb](http://sebarnold.net) to get yours listed, or [open an issue](https://github.com/learnables/learn2learn/issues/new).

1. **Uniform Sampling over Episode Difficulty**  [[ArXiv](https://arxiv.org/abs/2108.01662), [code](https://github.com/amazon-research/uniform-episodic-sampling)]
<br />
*S.M.R. Arnold\*, G. S. Dhillon\*, A. Ravichandran, S. Soatto*, NeurIPS 2021
<br />

2. **Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation** [[ArXiv](https://arxiv.org/abs/2106.09017), [code](https://github.com/AI-secure/multi-task-learning)]
<br />
*H. Wang, H. Zhao, B. Li*, ICML 2021
<br />

3. **Embedding Adaptation is Still Needed for Few-Shot Learning** [[ArXiv](https://arxiv.org/abs/2104.07255)]
<br />
*S.M.R. Arnold, F. Sha*, ArXiv 2021
<br />

4. **When MAML Can Adapt Fast and How to Assist When It Cannot** [[ArXiv](https://arxiv.org/abs/1910.13603), [code](https://github.com/Sha-Lab/kfo)]
<br />
*S.M.R. Arnold, S. Iqbal, F. Sha*, AISTATS 2021
<br />

5. **learn2learn: A Library for Meta-Learning Research** [[ArXiv](https://arxiv.org/abs/2008.12284), [code](https://github.com/learnables/learn2learn)]
<br />
*S.M.R. Arnold, P. Mahajan, D. Datta, I. Bunner, K.S. Zarkias*, ArXiv 2020
<br />
