AdaMatch-TF

Includes additional materials for the following keras.io blog post: Semi-supervision and domain adaptation with AdaMatch.

About the notebooks

• AdaMatch.ipynb: Original notebook submitted for the PR.
• Vanilla_WideResNet.ipynb: Trains a WideResNet-28-2 on MNIST (source domain) and evaluates on the SVHN dataset (target domain). The model trained in this notebook serves as the baseline.

Acknowledgements

• François Chollet for helping with the implementation.
• ML-GDE program for providing GCP credits that supported the experiments.

Paper citation

@misc{berthelot2021adamatch,
      title={AdaMatch: A Unified Approach to Semi-Supervised Learning and Domain Adaptation}, 
      author={David Berthelot and Rebecca Roelofs and Kihyuk Sohn and Nicholas Carlini and Alex Kurakin},
      year={2021},
      eprint={2106.04732},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}