| learnables/learn2learn |
2,283 |
|
0 |
1 |
almost 3 years ago |
19 |
February 10, 2022 |
13 |
mit |
Python |
| A PyTorch Library for Meta-learning Research |
| tristandeleu/pytorch-meta |
1,724 |
|
0 |
0 |
over 3 years ago |
28 |
September 20, 2021 |
53 |
mit |
Python |
| A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch |
| floodsung/LearningToCompare_FSL |
891 |
|
0 |
0 |
over 6 years ago |
0 |
|
20 |
mit |
Python |
| PyTorch code for CVPR 2018 paper: Learning to Compare: Relation Network for Few-Shot Learning (Few-Shot Learning part) |
| RL-VIG/LibFewShot |
771 |
|
0 |
0 |
about 2 years ago |
0 |
|
1 |
mit |
Python |
| LibFewShot: A Comprehensive Library for Few-shot Learning. TPAMI 2023. |
| sicara/easy-few-shot-learning |
737 |
|
0 |
0 |
over 2 years ago |
10 |
September 25, 2023 |
5 |
mit |
Python |
| Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification. |
| guan-yuan/awesome-AutoML-and-Lightweight-Models |
647 |
|
0 |
0 |
over 5 years ago |
0 |
|
0 |
|
|
| A list of high-quality (newest) AutoML works and lightweight models including 1.) Neural Architecture Search, 2.) Lightweight Structures, 3.) Model Compression, Quantization and Acceleration, 4.) Hyperparameter Optimization, 5.) Automated Feature Engineering. |
| tristandeleu/pytorch-maml-rl |
645 |
|
0 |
0 |
over 4 years ago |
0 |
|
20 |
mit |
Python |
| Reinforcement Learning with Model-Agnostic Meta-Learning in Pytorch |
| oscarknagg/few-shot |
520 |
|
0 |
0 |
over 6 years ago |
0 |
|
19 |
mit |
Python |
| Repository for few-shot learning machine learning projects |
| metaopt/torchopt |
460 |
|
0 |
2 |
over 2 years ago |
14 |
November 10, 2023 |
6 |
apache-2.0 |
Python |
| TorchOpt is an efficient library for differentiable optimization built upon PyTorch. |
| pykale/pykale |
415 |
|
0 |
0 |
about 2 years ago |
12 |
April 12, 2022 |
9 |
mit |
Python |
| Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the 🔥PyTorch ecosystem. ⭐ Star to support our work! |
