Transfer Learning Toolkit: Primers and Benchmarks

Fuzhen Zhuang, Keyu Duan, Tongjia Guo, Yongchun Zhu, Dongbo Xi +2 more
11/20/2019
cs.LGstat.ML

Official code: FuzhenZhuang/Transfer-Learning-Toolkit (109 stars, MIT, last commit 2021-06-11).

Abstract

The transfer learning toolkit wraps the codes of 17 transfer learning models and provides integrated interfaces, allowing users to use those models by calling a simple function. It is easy for primary researchers to use this toolkit and to choose proper models for real-world applications. The toolkit is written in Python and distributed under MIT open source license. In this paper, the current state of this toolkit is described and the necessary environment setting and usage are introduced.

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Code Implementations(1)

FuzhenZhuang/Transfer-Learning-ToolkitOfficial100%
MIT

Transfer Learning Toolkit for Primary Researchers

10937C, MNov 19, 20195 years agoMIT
toolkittransfer-learning

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Cite this paper

@article{zhuang2019transfer,
  title  = {Transfer Learning Toolkit: Primers and Benchmarks},
  author = {Fuzhen Zhuang and Keyu Duan and Tongjia Guo and Yongchun Zhu and Dongbo Xi and Zhiyuan Qi and Qing He},
  year   = {2019},
  eprint = {1911.08967},
  archivePrefix = {arXiv},
  url    = {https://arxiv.org/abs/1911.08967}
}

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