| Bridging few-shot learning and adaptation: new challenges of support-query shift E Bennequin, V Bouvier, M Tami, A Toubhans, C Hudelot Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 17 | 2021 |
| Learning to communicate in multi-agent reinforcement learning: A review MS Zaïem, E Bennequin arXiv preprint arXiv:1911.05438, 2019 | 12 | 2019 |
| Meta-learning algorithms for few-shot computer vision E Bennequin arXiv preprint arXiv:1909.13579, 2019 | 8 | 2019 |
| Few-shot image classification benchmarks are too far from reality: Build back better with semantic task sampling E Bennequin, M Tami, A Toubhans, C Hudelot Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 5 | 2022 |
| Open-set likelihood maximization for few-shot learning M Boudiaf, E Bennequin, M Tami, A Toubhans, P Piantanida, C Hudelot, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
| Model-Agnostic Few-Shot Open-Set Recognition M Boudiaf, E Bennequin, M Tami, C Hudelot, A Toubhans, P Piantanida, ... arXiv preprint arXiv:2206.09236, 2022 | 1 | 2022 |
| EasyFSL: Ready-to-use Code and Tutorial Notebooks for Few-Shot Image Classification E Bennequin https://github.com/sicara/easy-few-shot-learning, 2021 | | 2021 |
