Meta-Learning-Papers-with-Code

This repository contains a reading list of papers with code on Meta-Learning and Meta-Reinforcement-Learning, These papers are mainly categorized according to the type of model. In addition, I will separately list papers from important conferences starting from 2023, e.g., NIPS, ICML, ICLR, CVPR etc. This repository is still being continuously improved. If you have found any relevant papers that need to be included in this repository, please feel free to submit a pull request (PR) or open an issue.

Each paper may be applicable to one or more types of meta-learning frameworks, including optimization-based and metric-based, and may be applicable to multiple data sources, including image, text, audio, video, and multi-modality. These are marked in the type column. In addition, for different tasks and different problems, we have marked the SOTA algorithm separately. This is submitted with reference to the leadboard at the time of submission, and will be continuously modified. We provide a basic introduction to each paper to help you understand the work and core ideas of this article more quickly.

Label

🎭 Different Frameworks

• Meta-Learning.
• Meta-Reinforcement-Learning.

🎨 Different Types

• Optimization-based meta-learning approaches acquire a collection of optimal initial parameters, facilitating rapid convergence of a model when adapting to novel tasks.
• Metric-based meta-learning approaches acquire embedding functions that transform instances from various tasks, allowing them to be readily categorized using non-parametric methods.

✨ Different Data Sources

• Meta-Learning for CV (Images)
• Meta-Learning for CV (Videos)
• Meta-Learning for NLP
• Meta-Learning for Audio
• Meta-Learning for Multi-modal

It is worth noting that the experiments of some frameworks consist of multiple data sources. Our annotations are based on the paper description.

🚩 I have marked some recommended papers with 🌟/🎈 (SOTA methods/Just my personal preference 😉).

Survey.

Date	Method	Type	Conference	Paper Title and Paper Interpretation (In Chinese)	Code
2019	Book of Meta-Learning		Book	Meta-Learning (Automated Machine Learning)	None
2019	Learn dynamics		arXiv 2019	Meta-learners' learning dynamics are unlike learners'	None
2020	NLP		arXiv 2020	Meta-learning for few-shot natural language processing: A survey	None
2020	CV-classifier		IEEE Access	A literature survey and empirical study of meta-learning for classifier selection	None
2021	Learn 2 Learn		arXiv 2021	Meta-Learning: A Survey	None
2021	Learn 2 Learn 🎈		TPAMI	Meta-Learning in Neural Networks: A Survey	None
2021	Learn 2 Learn		Artif Intell Rev	A survey of deep meta-learning	None
2021	Learn 2 Learn		Current Opinion in Behavioral Sciences	Meta-learning in natural and artificial intelligence	None
2022	Multi-Modal		KBS	Multimodality in meta-learning: A comprehensive survey	None
2022	Image Segmentation		PR	Meta-seg: A survey of meta-learning for image segmentation	None
2022	Cyberspace Security		Digit. Commun. Netw.	Application of meta-learning in cyberspace security: A survey	None