@article{zhou2022domain,
  title={Domain generalization: A survey},
  author={Zhou, Kaiyang and Liu, Ziwei and Qiao, Yu and Xiang, Tao and Loy, Chen Change},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2022},
  publisher={IEEE}
}

@inproceedings{hoffman2018cycada,
  title={Cycada: Cycle-consistent adversarial domain adaptation},
  author={Hoffman, Judy and Tzeng, Eric and Park, Taesung and Zhu, Jun-Yan and Isola, Phillip and Saenko, Kate and Efros, Alexei and Darrell, Trevor},
  booktitle={International conference on machine learning},
  pages={1989--1998},
  year={2018},
  organization={Pmlr}
}

@inproceedings{ros2016synthia,
  title={The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes},
  author={Ros, German and Sellart, Laura and Materzynska, Joanna and Vazquez, David and Lopez, Antonio M},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={3234--3243},
  year={2016}
}

@article{sun2019learning,
  title={Learning part-based convolutional features for person re-identification},
  author={Sun, Yifan and Zheng, Liang and Li, Yali and Yang, Yi and Tian, Qi and Wang, Shengjin},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={43},
  number={3},
  pages={902--917},
  year={2019},
  publisher={IEEE}
}

@article{li2020scalable,
  title={Scalable person re-identification by harmonious attention},
  author={Li, Wei and Zhu, Xiatian and Gong, Shaogang},
  journal={International Journal of Computer Vision},
  volume={128},
  number={6},
  pages={1635--1653},
  year={2020},
  publisher={Springer}
}

@inproceedings{ganin2015unsupervised,
  title={Unsupervised domain adaptation by backpropagation},
  author={Ganin, Yaroslav and Lempitsky, Victor},
  booktitle={International conference on machine learning},
  pages={1180--1189},
  year={2015},
  organization={PMLR}
}

@inproceedings{li2018domain,
  title={Domain generalization with adversarial feature learning},
  author={Li, Haoliang and Pan, Sinno Jialin and Wang, Shiqi and Kot, Alex C},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={5400--5409},
  year={2018}
}

@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}
}

@inproceedings{li2018learning,
  title={Learning to generalize: Meta-learning for domain generalization},
  author={Li, Da and Yang, Yongxin and Song, Yi-Zhe and Hospedales, Timothy},
  booktitle={Proceedings of the AAAI conference on artificial intelligence},
  volume={32},
  number={1},
  year={2018}
}

@article{balaji2018metareg,
  title={Metareg: Towards domain generalization using meta-regularization},
  author={Balaji, Yogesh and Sankaranarayanan, Swami and Chellappa, Rama},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
}

@article{zhou2022domain,
  title={Domain generalization: A survey},
  author={Zhou, Kaiyang and Liu, Ziwei and Qiao, Yu and Xiang, Tao and Loy, Chen Change},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  year={2022},
  publisher={IEEE}
}

@inproceedings{li2017deeper,
  title={Deeper, broader and artier domain generalization},
  author={Li, Da and Yang, Yongxin and Song, Yi-Zhe and Hospedales, Timothy M},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={5542--5550},
  year={2017}
}

@inproceedings{ilse2020diva,
  title={Diva: Domain invariant variational autoencoders},
  author={Ilse, Maximilian and Tomczak, Jakub M and Louizos, Christos and Welling, Max},
  booktitle={Medical Imaging with Deep Learning},
  pages={322--348},
  year={2020},
  organization={PMLR}
}

@inproceedings{selvaraju2017grad,
  title={Grad-cam: Visual explanations from deep networks via gradient-based localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={618--626},
  year={2017}
}

% GradCAM
@inproceedings{selvaraju2017grad,
  title={Grad-cam: Visual explanations from deep networks via gradient-based localization},
  author={Selvaraju, Ramprasaath R and Cogswell, Michael and Das, Abhishek and Vedantam, Ramakrishna and Parikh, Devi and Batra, Dhruv},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={618--626},
  year={2017}
}

@article{lu2022gan,
  title={GAN-guided deformable attention network for identifying thyroid nodules in ultrasound images},
  author={Lu, Jintao and Ouyang, Xi and Shen, Xueda and Liu, Tianjiao and Cui, Zhiming and Wang, Qian and Shen, Dinggang},
  journal={IEEE Journal of Biomedical and Health Informatics},
  volume={26},
  number={4},
  pages={1582--1590},
  year={2022},
  publisher={IEEE}
}

@article{ouyang2020learning,
  title={Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis},
  author={Ouyang, Xi and Karanam, Srikrishna and Wu, Ziyan and Chen, Terrence and Huo, Jiayu and Zhou, Xiang Sean and Wang, Qian and Cheng, Jie-Zhi},
  journal={IEEE transactions on medical imaging},
  volume={40},
  number={10},
  pages={2698--2710},
  year={2020},
  publisher={IEEE}
}

@article{ouyang2020dual,
  title={Dual-sampling attention network for diagnosis of COVID-19 from community acquired pneumonia},
  author={Ouyang, Xi and Huo, Jiayu and Xia, Liming and Shan, Fei and Liu, Jun and Mo, Zhanhao and Yan, Fuhua and Ding, Zhongxiang and Yang, Qi and Song, Bin and others},
  journal={IEEE Transactions on Medical Imaging},
  volume={39},
  number={8},
  pages={2595--2605},
  year={2020},
  publisher={IEEE}
}

@article{lian2020attention,
  title={Attention-guided hybrid network for dementia diagnosis with structural MR images},
  author={Lian, Chunfeng and Liu, Mingxia and Pan, Yongsheng and Shen, Dinggang},
  journal={IEEE transactions on cybernetics},
  volume={52},
  number={4},
  pages={1992--2003},
  year={2020},
  publisher={IEEE}
}

@inproceedings{lian2019end,
  title={End-to-end dementia status prediction from brain mri using multi-task weakly-supervised attention network},
  author={Lian, Chunfeng and Liu, Mingxia and Wang, Li and Shen, Dinggang},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2019: 22nd International Conference, Shenzhen, China, October 13--17, 2019, Proceedings, Part IV 22},
  pages={158--167},
  year={2019},
  organization={Springer}
}

% Tell Me Where to Look: Guided Attention Inference Network
@inproceedings{li2018tell,
  title={Tell me where to look: Guided attention inference network},
  author={Li, Kunpeng and Wu, Ziyan and Peng, Kuan-Chuan and Ernst, Jan and Fu, Yun},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={9215--9223},
  year={2018}
}

@inproceedings{fukui2019attention,
  title={Attention branch network: Learning of attention mechanism for visual explanation},
  author={Fukui, Hiroshi and Hirakawa, Tsubasa and Yamashita, Takayoshi and Fujiyoshi, Hironobu},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={10705--10714},
  year={2019}
}

% A new grading system for the management of antenatal hydronephrosis
@article{dos2015new,
  title={A new grading system for the management of antenatal hydronephrosis},
  author={Dos Santos, Joana and Parekh, Rulan S and Piscione, Tino D and Hassouna, Tarek and Figueroa, Victor and Gonima, Paula and Vargas, Isis and Farhat, Walid and Rosenblum, Norman D},
  journal={Clinical Journal of the American Society of Nephrology},
  volume={10},
  number={10},
  pages={1783--1790},
  year={2015},
  publisher={Am Soc Nephrol}
}

@inproceedings{erdman2020predicting,
  title={Predicting obstructive hydronephrosis based on ultrasound alone},
  author={Erdman, Lauren and Skreta, Marta and Rickard, Mandy and McLean, Carson and Mezlini, Aziz and Keefe, Daniel T and Blais, Anne-Sophie and Brudno, Michael and Lorenzo, Armando and Goldenberg, Anna},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={493--503},
  year={2020},
  organization={Springer}
}

@article{smail2020using,
  title={Using deep learning algorithms to grade hydronephrosis severity: toward a clinical adjunct},
  author={Smail, Lauren C and Dhindsa, Kiret and Braga, Luis H and Becker, Suzanna and Sonnadara, Ranil R},
  journal={Frontiers in pediatrics},
  volume={8},
  pages={1},
  year={2020},
  publisher={Frontiers Media SA}
}

@inproceedings{tabrizi2021pediatric,
  title={Pediatric Hydronephrosis Severity Assessment Using Convolutional Neural Networks With Standardized Ultrasound Images},
  author={Tabrizi, Pooneh R and Zember, Jonathan and Sprague, Bruce Michael and Hoefer, Steven and Sanchez-Jacob, Ramon and Jago, James and Bulas, Dorothy and Pohl, Hans G and Linguraru, Marius George},
  booktitle={2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)},
  pages={1803--1806},
  year={2021},
  organization={IEEE}
}

@article{volpi2018generalizing,
  title={Generalizing to unseen domains via adversarial data augmentation},
  author={Volpi, Riccardo and Namkoong, Hongseok and Sener, Ozan and Duchi, John C and Murino, Vittorio and Savarese, Silvio},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
}

@inproceedings{volpi2019addressing,
  title={Addressing model vulnerability to distributional shifts over image transformation sets},
  author={Volpi, Riccardo and Murino, Vittorio},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={7980--7989},
  year={2019}
}

@article{xu2020robust,
  title={Robust and generalizable visual representation learning via random convolutions},
  author={Xu, Zhenlin and Liu, Deyi and Yang, Junlin and Raffel, Colin and Niethammer, Marc},
  journal={arXiv preprint arXiv:2007.13003},
  year={2020}
}

@inproceedings{xu2014exploiting,
  title={Exploiting low-rank structure from latent domains for domain generalization},
  author={Xu, Zheng and Li, Wen and Niu, Li and Xu, Dong},
  booktitle={Computer Vision--ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part III 13},
  pages={628--643},
  year={2014},
  organization={Springer}
}

@article{cha2021swad,
  title={Swad: Domain generalization by seeking flat minima},
  author={Cha, Junbum and Chun, Sanghyuk and Lee, Kyungjae and Cho, Han-Cheol and Park, Seunghyun and Lee, Yunsung and Park, Sungrae},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={22405--22418},
  year={2021}
}

@inproceedings{carlucci2019domain,
  title={Domain generalization by solving jigsaw puzzles},
  author={Carlucci, Fabio M and D'Innocente, Antonio and Bucci, Silvia and Caputo, Barbara and Tommasi, Tatiana},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={2229--2238},
  year={2019}
}

@article{bucci2021self,
  title={Self-supervised learning across domains},
  author={Bucci, Silvia and D’Innocente, Antonio and Liao, Yujun and Carlucci, Fabio M and Caputo, Barbara and Tommasi, Tatiana},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  volume={44},
  number={9},
  pages={5516--5528},
  year={2021},
  publisher={IEEE}
}

@article{wang2019learning,
  title={Learning robust representations by projecting superficial statistics out},
  author={Wang, Haohan and He, Zexue and Lipton, Zachary C and Xing, Eric P},
  journal={arXiv preprint arXiv:1903.06256},
  year={2019}
}

@inproceedings{huang2020self,
  title={Self-challenging improves cross-domain generalization},
  author={Huang, Zeyi and Wang, Haohan and Xing, Eric P and Huang, Dong},
  booktitle={Computer Vision--ECCV 2020: 16th European Conference, Glasgow, UK, August 23--28, 2020, Proceedings, Part II 16},
  pages={124--140},
  year={2020},
  organization={Springer}
}

% ResNet
@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition},
  pages={770--778},
  year={2016}
}

% ViT
@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{snoek2012practical,
  title={Practical bayesian optimization of machine learning algorithms},
  author={Snoek, Jasper and Larochelle, Hugo and Adams, Ryan P},
  journal={Advances in neural information processing systems},
  volume={25},
  year={2012}
}

@inproceedings{liu2020shape,
  title={Shape-aware meta-learning for generalizing prostate MRI segmentation to unseen domains},
  author={Liu, Quande and Dou, Qi and Heng, Pheng-Ann},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2020: 23rd International Conference, Lima, Peru, October 4--8, 2020, Proceedings, Part II 23},
  pages={475--485},
  year={2020},
  organization={Springer}
}

@inproceedings{he2015delving,
  title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
  author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
  booktitle={Proceedings of the IEEE international conference on computer vision},
  pages={1026--1034},
  year={2015}
}

@inproceedings{deng2009imagenet,
  title={Imagenet: A large-scale hierarchical image database},
  author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
  booktitle={2009 IEEE conference on computer vision and pattern recognition},
  pages={248--255},
  year={2009},
  organization={Ieee}
}

