@String(PAMI = {IEEE Trans. Pattern Anal. Mach. Intell.})
@String(IJCV = {Int. J. Comput. Vis.})
@String(CVPR= {IEEE Conf. Comput. Vis. Pattern Recog.})
@String(ICCV= {Int. Conf. Comput. Vis.})
@String(ECCV= {Eur. Conf. Comput. Vis.})
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@String(BMVC= {Brit. Mach. Vis. Conf.})
@String(TOG= {ACM Trans. Graph.})
@String(TIP  = {IEEE Trans. Image Process.})
@String(TVCG  = {IEEE Trans. Vis. Comput. Graph.})
@String(TMM  = {IEEE Trans. Multimedia})
@String(ACMMM= {ACM Int. Conf. Multimedia})
@String(ICME = {Int. Conf. Multimedia and Expo})
@String(ICASSP=	{ICASSP})
@String(ICIP = {IEEE Int. Conf. Image Process.})
@String(ACCV  = {ACCV})
@String(ICLR = {Int. Conf. Learn. Represent.})
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@String(PR   = {Pattern Recognition})
@String(AAAI = {AAAI})
@String(CVPRW= {IEEE Conf. Comput. Vis. Pattern Recog. Worksh.})
@String(CSVT = {IEEE Trans. Circuit Syst. Video Technol.})

@String(SPL	= {IEEE Sign. Process. Letters})
@String(VR   = {Vis. Res.})
@String(JOV	 = {J. Vis.})
@String(TVC  = {The Vis. Comput.})
@String(JCST  = {J. Comput. Sci. Tech.})
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@String(PAMI  = {IEEE TPAMI})
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}

@article{sagawa2019distributionally,
  title={Distributionally robust neural networks for group shifts: On the importance of regularization for worst-case generalization},
  author={Sagawa, Shiori and Koh, Pang Wei and Hashimoto, Tatsunori B and Liang, Percy},
  journal={arXiv preprint arXiv:1911.08731},
  year={2019}
}
@inproceedings{liu2021cycle,
  title={Cycle self-training for domain adaptation},
  author={Liu, Hong and Wang, Jianmin and Long, Mingsheng},
  booktitle={Advances in Neural Information Processing Systems},
  volume={34},
  pages={22968--22981},
  year={2021}
}

@inproceedings{zhang2023adanpc,
  title={AdaNPC: Exploring Non-Parametric Classifier for Test-Time Adaptation},
  author={Zhang, Yifan and Wang, Xue and Jin, Kexin and Yuan, Kun and Zhang, Zhang and Wang, Liang and Jin, Rong and Tan, Tieniu},
  booktitle={International Conference on Machine Learning},
  pages={41647--41676},
  year={2023},
  organization={PMLR}
}


@inproceedings{shin2022mm,
  title={MM-TTA: multi-modal test-time adaptation for 3d semantic segmentation},
  author={Shin, Inkyu and Tsai, Yi-Hsuan and Zhuang, Bingbing and Schulter, Samuel and Liu, Buyu and Garg, Sparsh and Kweon, In So and Yoon, Kuk-Jin},
  booktitle={IEEE Conference on Computer Vision and Pattern Recognition},
  pages={16928--16937},
  year={2022}
}

@article{yang2022dltta,
  title={DLTTA: Dynamic Learning Rate for Test-time Adaptation on Cross-domain Medical Images},
  author={Yang, Hongzheng and Chen, Cheng and Jiang, Meirui and Liu, Quande and Cao, Jianfeng and Heng, Pheng Ann and Dou, Qi},
  journal={IEEE Transactions on Medical Imaging},
  volume={41},
  number={12},
  pages={3575--3586},
  year={2022},
  publisher={IEEE}
}

@article{wang2023feature,
  title={Feature Alignment and Uniformity for Test Time Adaptation},
  author={Wang, Shuai and Zhang, Daoan and Yan, Zipei and Zhang, Jianguo and Li, Rui},
  journal={arXiv preprint arXiv:2303.10902},
  year={2023}
}


@inproceedings{yi2023source,
  title={When Source-Free Domain Adaptation Meets Learning with Noisy Labels},
  author={Yi, Li and Xu, Gezheng and Xu, Pengcheng and Li, Jiaqi and Pu, Ruizhi and Ling, Charles and McLeod, A Ian and Wang, Boyu},
  booktitle={International Conference on Learning Representations},
  year={2023}
}

@article{liang2023comprehensive,
  title={A Comprehensive Survey on Test-Time Adaptation under Distribution Shifts},
  author={Liang, Jian and He, Ran and Tan, Tieniu},
  journal={arXiv preprint arXiv:2303.15361},
  year={2023}
}

@article{zhou2021domain,
  title={Domain adaptive ensemble learning},
  author={Zhou, Kaiyang and Yang, Yongxin and Qiao, Yu and Xiang, Tao},
  journal={IEEE Transactions on Image Processing},
  volume={30},
  pages={8008--8018},
  year={2021},
  publisher={IEEE}
}

@inproceedings{litrico2023guiding,
  title={Guiding Pseudo-Labels With Uncertainty Estimation for Source-Free Unsupervised Domain Adaptation},
  author={Litrico, Mattia and Del Bue, Alessio and Morerio, Pietro},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={7640--7650},
  year={2023}
}

@article{blanchard2021domain,
  title={Domain generalization by marginal transfer learning},
  author={Blanchard, Gilles and Deshmukh, Aniket Anand and Dogan, {\"U}run and Lee, Gyemin and Scott, Clayton},
  journal={The Journal of Machine Learning Research},
  volume={22},
  number={1},
  pages={46--100},
  year={2021},
  publisher={JMLRORG}
}

@inproceedings{li2018deep,
  title={Deep domain generalization via conditional invariant adversarial networks},
  author={Li, Ya and Tian, Xinmei and Gong, Mingming and Liu, Yajing and Liu, Tongliang and Zhang, Kun and Tao, Dacheng},
  booktitle={Proceedings of the European conference on computer vision (ECCV)},
  pages={624--639},
  year={2018}
}

@article{ganin2016domain,
  title={Domain-adversarial training of neural networks},
  author={Ganin, Yaroslav and Ustinova, Evgeniya and Ajakan, Hana and Germain, Pascal and Larochelle, Hugo and Laviolette, Fran{\c{c}}ois and Marchand, Mario and Lempitsky, Victor},
  journal={The journal of machine learning research},
  volume={17},
  number={1},
  pages={2096--2030},
  year={2016},
  publisher={JMLR. org}
}

@inproceedings{peng2019moment,
  title={Moment matching for multi-source domain adaptation},
  author={Peng, Xingchao and Bai, Qinxun and Xia, Xide and Huang, Zijun and Saenko, Kate and Wang, Bo},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={1406--1415},
  year={2019}
}




@book{vapnik1998statistical,
  title={Statistical Learning Theory},
  author={Vladimir Vapnik},
  year={1998},
  publisher={Wiley-Interscience},
  edition={1st},
  pages={768},
  isbn={0471030031}
}

@misc{wiki:johnson-lindenstrauss,
  howpublished = "\url{https://wikipedia.org/wiki/Lemma_von_Johnson-Lindenstrauss}",
}

@article{freksen2021introduction,
  title={An introduction to johnson-lindenstrauss transforms},
  author={Freksen, Casper Benjamin},
  journal={arXiv preprint arXiv:2103.00564},
  year={2021}
}
@article{rajpurkar2017chexnet,
  title={Chexnet: Radiologist-level pneumonia detection on chest x-rays with deep learning},
  author={Rajpurkar, Pranav and Irvin, Jeremy and Zhu, Kaylie and Yang, Brandon and Mehta, Hershel and Duan, Tony and Ding, Daisy and Bagul, Aarti and Langlotz, Curtis and Shpanskaya, Katie and others},
  journal={arXiv preprint arXiv:1711.05225},
  year={2017}
}

@article{hannun2019cardiologist,
  title={Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network},
  author={Hannun, Awni Y and Rajpurkar, Pranav and Haghpanahi, Masoumeh and Tison, Geoffrey H and Bourn, Codie and Turakhia, Mintu P and Ng, Andrew Y},
  journal={Nature medicine},
  volume={25},
  number={1},
  pages={65--69},
  year={2019},
  publisher={Nature Publishing Group US New York}
}

@article{rajpurkar2018deep,
  title={Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists},
  author={Rajpurkar, Pranav and Irvin, Jeremy and Ball, Robyn L and Zhu, Kaylie and Yang, Brandon and Mehta, Hershel and Duan, Tony and Ding, Daisy and Bagul, Aarti and Langlotz, Curtis P and others},
  journal={PLoS medicine},
  volume={15},
  number={11},
  pages={e1002686},
  year={2018},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{guan2021domain,
  title={Domain adaptation for medical image analysis: a survey},
  author={Guan, Hao and Liu, Mingxia},
  journal={IEEE Transactions on Biomedical Engineering},
  volume={69},
  number={3},
  pages={1173--1185},
  year={2021},
  publisher={IEEE}
}

@article{vapnik1991principles,
  title={Principles of risk minimization for learning theory},
  author={Vapnik, Vladimir},
  journal={Advances in neural information processing systems},
  volume={4},
  year={1991}
}

@inproceedings{johnson1984extensions,
  title={Extensions of Lipshitz mapping into Hilbert space},
  author={Johnson, William B},
  booktitle={Conference modern analysis and probability, 1984},
  pages={189--206},
  year={1984}
}

@article{huang2023fourier,
  title={Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification},
  author={Huang, Yuhao and Yang, Xin and Huang, Xiaoqiong and Zhou, Xinrui and Chi, Haozhe and Dou, Haoran and Hu, Xindi and Wang, Jian and Deng, Xuedong and Ni, Dong},
  journal={arXiv preprint arXiv:2306.02544},
  year={2023}
}

% MESSIDOR dataset
@article{decenciere2014feedback,
  title={Feedback on a publicly distributed image database: the Messidor database},
  author={Decenci{\`e}re, Etienne and Zhang, Xiwei and Cazuguel, Guy and Lay, Bruno and Cochener, B{\'e}atrice and Trone, Caroline and Gain, Philippe and Ordonez, Richard and Massin, Pascale and Erginay, Ali and others},
  journal={Image Analysis \& Stereology},
  volume={33},
  number={3},
  pages={231--234},
  year={2014}
}

% Fetal-8
@article{burgos2020evaluation,
  title={Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes},
  author={Burgos-Artizzu, Xavier P and Coronado-Guti{\'e}rrez, David and Valenzuela-Alcaraz, Brenda and Bonet-Carne, Elisenda and Eixarch, Elisenda and Crispi, Fatima and Gratac{\'o}s, Eduard},
  journal={Scientific Reports},
  volume={10},
  number={1},
  pages={10200},
  year={2020},
  publisher={Nature Publishing Group UK London}
}


@article{kumar2019verified,
  title={Verified uncertainty calibration},
  author={Kumar, Ananya and Liang, Percy S and Ma, Tengyu},
  journal={Advances in Neural Information Processing Systems},
  volume={32},
  year={2019}
}


% shifts lead to failure
@article{roschewitz2023automatic,
  title={Automatic correction of performance drift under acquisition shift in medical image classification},
  author={Roschewitz, M{\'e}lanie and Khara, Galvin and Yearsley, Joe and Sharma, Nisha and James, Jonathan J and Ambr{\'o}zay, {\'E}va and Heroux, Adam and Kecskemethy, Peter and Rijken, Tobias and Glocker, Ben},
  journal={Nature Communications},
  volume={14},
  number={1},
  pages={6608},
  year={2023},
  publisher={Nature Publishing Group UK London}
}


@article{dosovitskiy2020image,
  title={An image is worth 16x16 words: Transformers for image recognition at scale},
  author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and others},
  journal={arXiv preprint arXiv:2010.11929},
  year={2020}
}

@article{ambekar2023learning,
  title={Learning Variational Neighbor Labels for Test-Time Domain Generalization},
  author={Ambekar, Sameer and Xiao, Zehao and Shen, Jiayi and Zhen, Xiantong and Snoek, Cees GM},
  journal={arXiv preprint arXiv:2307.04033},
  year={2023}
}

@inproceedings{naeini2015obtaining,
  title={Obtaining well calibrated probabilities using bayesian binning},
  author={Naeini, Mahdi Pakdaman and Cooper, Gregory and Hauskrecht, Milos},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={29},
  year={2015}
}

