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https://github.com/alro10/meta-learning-resources
A curated list of meta-learning resources: papers, coding, tutorials, etc.
https://github.com/alro10/meta-learning-resources
deep-reinforcement-learning meta-learning reinforcement-learning
Last synced: about 1 month ago
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A curated list of meta-learning resources: papers, coding, tutorials, etc.
- Host: GitHub
- URL: https://github.com/alro10/meta-learning-resources
- Owner: Alro10
- License: apache-2.0
- Created: 2019-05-15T02:01:13.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2019-12-02T12:55:28.000Z (about 5 years ago)
- Last Synced: 2024-06-25T06:32:47.215Z (6 months ago)
- Topics: deep-reinforcement-learning, meta-learning, reinforcement-learning
- Homepage:
- Size: 130 KB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Meta-Learning Resources
A curated list of meta-learning papers, code, tutorials, etc.Under developing!
*Figure by BAIR Lab*
## [Table of Contents]()
* [Papers](#Papers)
* [Tutorials](#Tutorials)
* [Code](#Resources)## Papers
### 2019
- [Meta-Learning of Neural Architectures for Few-Shot Learning](https://arxiv.org/pdf/1911.11090.pdf)
- Thomas Elsken, et al.
- not yet- [Meta-Q-Learning](https://arxiv.org/pdf/1910.00125.pdf)
- Code-not yet
- Rasool Fakoor, et al.- [Meta-Learning with Implicit Gradients](https://arxiv.org/pdf/1909.04630.pdf) **NeurIPS 2019. First two authors contributed equally**
- Aravind Rajeswaran, Chelsea Finn, Sham Kakade, Sergey Levine.
- Code- not yet- [Metalearned Neural Memory](https://arxiv.org/abs/1907.09720).
- Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler.
- Code- not yet- [Meta-Transfer Learning for Few-Shot Learning](https://arxiv.org/abs/1812.02391). **CVPR 2019**
- Qianru Sun, Yaoyao Liu, Tat-Seng Chua, Bernt Schiele.
- [[Code-TensorFlow](https://github.com/y2l/meta-transfer-learning-tensorflow)]
- [[Code-Pytorch]([email protected]:Alro10/meta-learning-resources.git)]- [Meta-learning with differentiable closed-form solvers](https://arxiv.org/abs/1805.08136). **ICLR 2019**
- Luca Bertinetto, João F. Henriques, Philip H.S. Torr, Andrea Vedaldi.
- [[Code](https://github.com/bertinetto/r2d2)]- [Meta reinforcement learning as task inference](https://arxiv.org/abs/1905.06424). **DeepMind**
- Jan Humplik, Alexandre Galashov, LeonardDeepMind Hasenclever, Pedro A. Ortega, Yee Whye Teh, Nicolas Heess.
### 2018
- [Meta-Reinforcement Learning of Structured Exploration Strategies](https://papers.nips.cc/paper/7776-meta-reinforcement-learning-of-structured-exploration-strategies.pdf). **NeurIPS 2018**
- Abhishek Gupta, Russell Mendonca, YuXuan Liu, Pieter Abbeel, Sergey Levine.
### 2017
- [Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks](https://arxiv.org/abs/1703.03400). **ICML 2017**
- Chelsea Finn, Pieter Abbeel, Sergey Levine.
- [[Code](https://github.com/cbfinn/maml)]## Code
- [TensorFlow 2.0 implementation of MAML](https://github.com/mari-linhares/tensorflow-maml) by Marianne Linhares.