Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
| Date | Stars |
|---|---|
| 2026-07-24 | 14343 |
| 2026-07-25 | 14343 |
| 2026-07-28 | 14343 |
| 2026-07-30 | 14343 |
| 2026-08-06 | 14343 |
Today
— stars today
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Momentum
0.0
growth rate 0.00%/day
[![Contributors][contributors-shield]][contributors-url]
[![Forks][forks-shield]][forks-url]
[![Stargazers][stars-shield]][stars-url]
[![Issues][issues-shield]][issues-url]
<h1 align="center">
<br>
<img src="png/logo.jpg" alt="Transfer Leanring" width="500">
</h1>
<h4 align="center">Everything about Transfer Learning. 迁移学习.</h4>
<p align="center">
<strong><a href="#0papers-论文">Papers</a></strong> •
<strong><a href="#1introduction-and-tutorials-简介与教程">Tutorials</a></strong> •
<a href="#2transfer-learning-areas-and-papers-研究领域与相关论文">Research areas</a> •
<a href="#3theory-and-survey-理论与综述">Theory</a> •
<a href="#3theory-and-survey-理论与综述">Survey</a> •
<strong><a href="https://github.com/jindongwang/transferlearning/tree/master/code">Code</a></strong> •
<strong><a href="#7datasets-and-benchmarks-数据集与评测结果">Dataset & benchmark</a></strong>
</p>
<p align="center">
<a href="#6transfer-learning-thesis-硕博士论文">Thesis</a> •
<a href="#5transfer-learning-scholars-著名学者">Scholars</a> •
<a href="#8transfer-learning-challenges-迁移学习比赛">Contests</a> •
<a href="#journals-and-conferences">Journal/conference</a> •
<a href="#applications-迁移学习应用">Applications</a> •
<a href="#other-resources-其他资源">Others</a> •
<a href="#contributing-欢迎参与贡献">Contributing</a>
</p>
**Widely used by top conferences and journals:**
- Conferences: [[CVPR'22](https://openaccess.thecvf.com/content/CVPR2022W/FaDE-TCV/html/Zhang_Segmenting_Across_Places_The_Need_for_Fair_Transfer_Learning_With_CVPRW_2022_paper.html)] [[NeurIPS'21](https://proceedings.neurips.cc/paper/2021/file/731b03008e834f92a03085ef47061c4a-Paper.pdf)] [[IJCAI'21](https://arxiv.org/abs/2103.03097)] [[ESEC/FSE'20](https://dl.acm.org/doi/abs/10.1145/3368089.3409696)] [[IJCNN'20](https://ieeexplore.ieee.org/abstract/document/9207556)] [[ACMMM'18](https://dl.acm.org/doi/abs/10.1145/3240508.3240512)] [[ICME'19](https://ieeexplore.ieee.org/abstract/document/8784776/)]
- Journals: [[IEEE TKDE](https://ieeexplore.ieee.org/abstract/document/9782500/)] [[ACM TIST](https://dl.acm.org/doi/abs/10.1145/3360309)] [[Information sciences](https://www.sciencedirect.com/science/article/pii/S0020025520308458)] [[Neurocomputing](https://www.sciencedirect.com/science/article/pii/S0925231221007025)] [[IEEE Transactions on Cognitive and Developmental Systems](https://ieeexplore.ieee.org/abstract/document/9659817)]
```
@Misc{transferlearning.xyz,
howpublished = {\url{http://transferlearning.xyz}},
title = {Everything about Transfer Learning and Domain Adapation},
author = {Wang, Jindong and others}
}
```
[](https://awesome.re) [](https://opensource.org/licenses/MIT) [](https://github.com/996icu/996.ICU/blob/master/LICENSE) [](https://996.icu)
Related Codes:
- Large language model evaluation: [[llm-eval](https://llm-eval.github.io/)]
- Large language model enhancement: [[llm-enhance](https://llm-enhance.github.io/)]
- Robust machine learning: [[robustlearn: robust machine learning](https://github.com/microsoft/robustlearn)]
- Semi-supervised learning: [[USB: unified semi-supervised learning benchmark](https://github.com/microsoft/Semi-supervised-learning)] | [[TorchSSL: a unified SSL library](https://github.com/TorchSSL/TorchSSL)]
- LLM benchmark: [[PromptBench: adversarial robustness of prompts of LLMs](https://github.com/microsoft/promptbench)]
- Federated learning: [[PersonalizedFL: library for personalized federated learning](https://github.com/microsoft/PersonalizedFL)]
- Activity recognition and machine learning [[Activity recognition](https://github.com/jindongwang/activityrecognition)]｜[[Machine learning](https://github.com/jindongwang/MachineLearning)]
- - -
**NOTE:** You can directly open the code in [Gihub Codespaces](https://docExcerpt of 21,549 characters
Read on GitHub
Jindong Wang · @microsoft · China
979
24
Wenxin
23
18
15
10
8
5
5
Kaiyang
3
3
zengxianfang · Zhejiang university · China
3
Werner Zellinger · Johannes Kepler University Linz · Austria
3
Malinda
3
cven · China
2
Lu Yan · NYU · United States
2
shandianchengzi · Hua Zhong University Of Science and Technology · China
2
2
Vinod K Kurmi · IISER Bhopal
2
Min-Hung (Steve) Chen · @NVIDIA · Taiwan
2
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:97436820ce0e6eae, topic:deep-learning
matched fp:97436820ce0e6eae, topic:representation-learning
matched fp:97436820ce0e6eae, topic:papers