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UniDA_CGL

Code release for Curriculum Adaptation Method Based on Graph Neural Networks for Universal Domain Adaptation.

If you have any problem about our code, feel free to contact [email protected] or describe your problem in issues.

We reuse some basic code in Progressive Graph Learning for Open-Set Domain Adaptation (https://github.com/BUserName/PGL) and dalib (https://dalib.readthedocs.io/en/latest/tutorial.html).

We would like to express our sincere gratitude to the authors of PGL and dalib for their contributions to the domain adaptation community.

All the code about the part declared as novelty in this paper is done by ourselves.

unida_cgl's People

Contributors

fancangning avatar

Stargazers

Xiang (Angelo) Fang, 方翔 avatar Guowei ZHANG (张国伟) avatar

Watchers

 avatar Kostas Georgiou avatar

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