@article{song2020score,
  title={Score-based generative modeling through stochastic differential equations},
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  year={2020}
}

@article{jiang2022dp,
  title={DP$^2$ -VAE: Differentially Private Pre-trained Variational Autoencoders},
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  year={2022}
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@inproceedings{abadi2016deep,
  title={Deep learning with differential privacy},
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@article{dockhorn2022differentially,
  title={Differentially private diffusion models},
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  year={2022}
}

@inproceedings{dwork2006calibrating,
  title={Calibrating noise to sensitivity in private data analysis},
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@inproceedings{goodfellow2014generative,
  title={Generative adversarial nets},
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@article{song2019generative,
  title={Generative modeling by estimating gradients of the data distribution},
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}
@inproceedings{sohl2015deep,
  title={Deep unsupervised learning using nonequilibrium thermodynamics},
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@article{van2021memorization,
  title={On memorization in probabilistic deep generative models},
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  year={2021}
}

@article{anderson1982reverse,
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@misc{carlini2023extracting,
      title={Extracting Training Data from Diffusion Models}, 
      author={Nicholas Carlini and Jamie Hayes and Milad Nasr and Matthew Jagielski and Vikash Sehwag and Florian Tramèr and Borja Balle and Daphne Ippolito and Eric Wallace},
      year={2023},
      eprint={2301.13188},
      archivePrefix={arXiv},
      primaryClass={cs.CR}
}
@article{DBLP:journals/corr/abs-2110-14795,
  author       = {Jiancheng Yang and
                  Rui Shi and
                  Donglai Wei and
                  Zequan Liu and
                  Lin Zhao and
                  Bilian Ke and
                  Hanspeter Pfister and
                  Bingbing Ni},
  title        = {MedMNIST v2: {A} Large-Scale Lightweight Benchmark for 2D and 3D Biomedical
                  Image Classification},
  journal      = {CoRR},
  volume       = {abs/2110.14795},
  year         = {2021},
  url          = {https://arxiv.org/abs/2110.14795},
  eprinttype    = {arXiv},
  eprint       = {2110.14795},
  timestamp    = {Mon, 27 Jun 2022 07:55:41 +0200},
  biburl       = {https://dblp.org/rec/journals/corr/abs-2110-14795.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}

@inproceedings{resnet50,
  title={Deep residual learning for image recognition},
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  year={2016}
}

@inproceedings{loshchilov2019decoupled,
  author       = {Ilya Loshchilov and
                  Frank Hutter},
  title        = {Decoupled Weight Decay Regularization},
  booktitle    = {7th International Conference on Learning Representations, {ICLR} 2019,
                  New Orleans, LA, USA, May 6-9, 2019},
  publisher    = {OpenReview.net},
  year         = {2019},
  url          = {https://openreview.net/forum?id=Bkg6RiCqY7},
  timestamp    = {Thu, 25 Jul 2019 14:26:04 +0200},
  biburl       = {https://dblp.org/rec/conf/iclr/LoshchilovH19.bib},
  bibsource    = {dblp computer science bibliography, https://dblp.org}
}
@article{dhariwal2021diffusion,
  title={Diffusion models beat gans on image synthesis},
  author={Dhariwal, Prafulla and Nichol, Alexander},
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  volume={34},
  pages={8780--8794},
  year={2021}
}
@article{cong2020gan,
	title={Gan memory with no forgetting},
	author={Cong, Yulai and Zhao, Miaoyun and Li, Jianqiao and Wang, Sijia and Carin, Lawrence},
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	volume={33},
	pages={16481--16494},
	year={2020}
}
@article{jin2019review,
	title={A review of secure and privacy-preserving medical data sharing},
	author={Jin, Hao and Luo, Yan and Li, Peilong and Mathew, Jomol},
	journal={IEEE Access},
	volume={7},
	pages={61656--61669},
	year={2019},
	publisher={IEEE}
}
@article{larrazabal2020gender,
	title={Gender imbalance in medical imaging datasets produces biased classifiers for computer-aided diagnosis},
	author={Larrazabal, Agostina J and Nieto, Nicol{\'a}s and Peterson, Victoria and Milone, Diego H and Ferrante, Enzo},
	journal={Proceedings of the National Academy of Sciences},
	volume={117},
	number={23},
	pages={12592--12594},
	year={2020},
	publisher={National Acad Sciences}
}
@article{wang2022metateacher,
	title={MetaTeacher: Coordinating Multi-Model Domain Adaptation for Medical Image Classification},
	author={Wang, Zhenbin and Ye, Mao and Zhu, Xiatian and Peng, Liuhan and Tian, Liang and Zhu, Yingying},
	journal={Advances in Neural Information Processing Systems},
	volume={35},
	pages={20823--20837},
	year={2022}
}
@inproceedings{chen2021multi,
	title={Multi-initialization meta-learning with domain adaptation},
	author={Chen, Zhengyu and Wang, Donglin},
	booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	pages={1390--1394},
	year={2021},
	organization={IEEE}
}
@inproceedings{pinaya2022brain,
	title={Brain imaging generation with latent diffusion models},
	author={Pinaya, Walter HL and Tudosiu, Petru-Daniel and Dafflon, Jessica and Da Costa, Pedro F and Fernandez, Virginia and Nachev, Parashkev and Ourselin, Sebastien and Cardoso, M Jorge},
	booktitle={Deep Generative Models: Second MICCAI Workshop, DGM4MICCAI 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings},
	pages={117--126},
	year={2022},
	organization={Springer}
}
@article{ruiz2022dreambooth,
	title={Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation},
	author={Ruiz, Nataniel and Li, Yuanzhen and Jampani, Varun and Pritch, Yael and Rubinstein, Michael and Aberman, Kfir},
	journal={arXiv preprint arXiv:2208.12242},
	year={2022}
}

@misc{meng2023distillation,
      title={On Distillation of Guided Diffusion Models}, 
      author={Chenlin Meng and Robin Rombach and Ruiqi Gao and Diederik P. Kingma and Stefano Ermon and Jonathan Ho and Tim Salimans},
      year={2023},
      eprint={2210.03142},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
@inproceedings{wolleb2022diffusion,
  title={Diffusion models for medical anomaly detection},
  author={Wolleb, Julia and Bieder, Florentin and Sandk{\"u}hler, Robin and Cattin, Philippe C},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2022: 25th International Conference, Singapore, September 18--22, 2022, Proceedings, Part VIII},
  pages={35--45},
  year={2022},
  organization={Springer}
}
@misc{von-platen-etal-2022-diffusers,
  author = {Patrick von Platen and Suraj Patil and Anton Lozhkov and Pedro Cuenca and Nathan Lambert and Kashif Rasul and Mishig Davaadorj and Thomas Wolf},
  title = {Diffusers: State-of-the-art diffusion models},
  year = {2022},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished = {\url{https://github.com/huggingface/diffusers}}
}

@inproceedings{somepalli2023diffusion,
  title={Diffusion art or digital forgery? investigating data replication in diffusion models},
  author={Somepalli, Gowthami and Singla, Vasu and Goldblum, Micah and Geiping, Jonas and Goldstein, Tom},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={6048--6058},
  year={2023}
}
@misc{nichol2021improved,
      title={Improved Denoising Diffusion Probabilistic Models}, 
      author={Alex Nichol and Prafulla Dhariwal},
      year={2021},
      eprint={2102.09672},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}
@misc{karras2018progressive,
      title={Progressive Growing of GANs for Improved Quality, Stability, and Variation}, 
      author={Tero Karras and Timo Aila and Samuli Laine and Jaakko Lehtinen},
      year={2018},
      eprint={1710.10196},
      archivePrefix={arXiv},
      primaryClass={cs.NE}
}
@misc{su2023dual,
      title={Dual Diffusion Implicit Bridges for Image-to-Image Translation}, 
      author={Xuan Su and Jiaming Song and Chenlin Meng and Stefano Ermon},
      year={2023},
      eprint={2203.08382},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
@inproceedings{chou2023backdoor,
  title={How to backdoor diffusion models?},
  author={Chou, Sheng-Yen and Chen, Pin-Yu and Ho, Tsung-Yi},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={4015--4024},
  year={2023}
}
@article{kirillov2023segment,
  title={Segment anything},
  author={Kirillov, Alexander and Mintun, Eric and Ravi, Nikhila and Mao, Hanzi and Rolland, Chloe and Gustafson, Laura and Xiao, Tete and Whitehead, Spencer and Berg, Alexander C and Lo, Wan-Yen and others},
  journal={arXiv preprint arXiv:2304.02643},
  year={2023}
}
@article{nasr2023scalable,
  title={Scalable extraction of training data from (production) language models},
  author={Nasr, Milad and Carlini, Nicholas and Hayase, Jonathan and Jagielski, Matthew and Cooper, A Feder and Ippolito, Daphne and Choquette-Choo, Christopher A and Wallace, Eric and Tram{\`e}r, Florian and Lee, Katherine},
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  year={2023}
}
@article{carlini2022quantifying,
  title={Quantifying memorization across neural language models},
  author={Carlini, Nicholas and Ippolito, Daphne and Jagielski, Matthew and Lee, Katherine and Tramer, Florian and Zhang, Chiyuan},
  journal={arXiv preprint arXiv:2202.07646},
  year={2022}
}
@inproceedings{carlini2021extracting,
  title={Extracting training data from large language models},
  author={Carlini, Nicholas and Tramer, Florian and Wallace, Eric and Jagielski, Matthew and Herbert-Voss, Ariel and Lee, Katherine and Roberts, Adam and Brown, Tom and Song, Dawn and Erlingsson, Ulfar and others},
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@article{johnson2019mimic,
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@InProceedings{wang2017chestxray,
author = {Wang, Xiaosong and Peng, Yifan and Lu, Le and Lu, Zhiyong and Bagheri, Mohammadhadi
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title = {ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised
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year = {2017}
}
@inproceedings{bai2021training,
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  pages={2534--2542},
  year={2021}
}

@article{dar2024unconditional,
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@article{stein2024exposing,
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  year={2024}
}
@inproceedings{Cohen2022xrv,
title = {{TorchXRayVision: A library of chest X-ray datasets and models}},
author = {Cohen, Joseph Paul and Viviano, Joseph D. and Bertin, Paul and Morrison, Paul and Torabian, Parsa and Guarrera, Matteo and Lungren, Matthew P and Chaudhari, Akshay and Brooks, Rupert and Hashir, Mohammad and Bertrand, Hadrien},
booktitle = {Medical Imaging with Deep Learning},
url = {https://github.com/mlmed/torchxrayvision},
arxivId = {2111.00595},
year = {2022}
}
@inproceedings{ren2024unveiling,
  title={Unveiling and mitigating memorization in text-to-image diffusion models through cross attention},
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@InProceedings{Liu_2022_CVPR,
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    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month     = {June},
    year      = {2022},
    pages     = {1815-1824}
}
ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks onWeakly-Supervised Classification and Localization of Common Thorax Diseases
@inproceedings{wang2017chestx,
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  year={2017}
}
@misc{odir,
  author = {{Peking University}},
  title = {Peking University International Competition on Ocular Disease Intelligent Recognition (ODIR-2019)},
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  howpublished = {\url{https:llodir2019.grand-challenge.org/dataset}},
  note = {Accessed: 2024-02-19}
}

@inproceedings{kingma2013auto,
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@article{goodfellow2020generative,
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@inproceedings{rombach2022high,
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}

@article{ho2020denoising,
  title={Denoising diffusion probabilistic models},
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@article{xie2018differentially,
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  year={2018}
}

@article{song2020denoising,
  title={Denoising diffusion implicit models},
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}

@inproceedings{hamamci2025generatect,
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  booktitle={ECCV'24},
  pages={126--143},
  year={2025},
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}

@article{guo2024maisi,
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  year={2024},
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@misc{ronneberger2015unet,
      title={U-Net: Convolutional Networks for Biomedical Image Segmentation}, 
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      archivePrefix={arXiv},
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@misc{dombrowski2023tradeoffs,
      title={Trade-offs in Fine-tuned Diffusion Models Between Accuracy and Interpretability}, 
      author={Mischa Dombrowski and Hadrien Reynaud and Johanna P. Müller and Matthew Baugh and Bernhard Kainz},
      year={2023},
      eprint={2303.17908},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
@inproceedings{baugh2023many,
  title={Many tasks make light work: Learning to localise medical anomalies from multiple synthetic tasks},
  author={Baugh, Matthew and Tan, Jeremy and M{\"u}ller, Johanna P and Dombrowski, Mischa and Batten, James and Kainz, Bernhard},
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  pages={162--172},
  year={2023},
  organization={Springer}
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@article{reynaud2023feature,
  title={Feature-Conditioned Cascaded Video Diffusion Models for Precise Echocardiogram Synthesis},
  author={Reynaud, Hadrien and Qiao, Mengyun and Dombrowski, Mischa and Day, Thomas and Razavi, Reza and Gomez, Alberto and Leeson, Paul and Kainz, Bernhard},
  journal={arXiv preprint arXiv:2303.12644},
  year={2023}
}
@misc{chambon2022roentgen,
      title={RoentGen: Vision-Language Foundation Model for Chest X-ray Generation}, 
      author={Pierre Chambon and Christian Bluethgen and Jean-Benoit Delbrouck and Rogier Van der Sluijs and Małgorzata Połacin and Juan Manuel Zambrano Chaves and Tanishq Mathew Abraham and Shivanshu Purohit and Curtis P. Langlotz and Akshay Chaudhari},
      year={2022},
      eprint={2211.12737},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}
@inproceedings{dombrowski2023foreground,
  title={Foreground-background separation through concept distillation from generative image foundation models},
  author={Dombrowski, Mischa and Reynaud, Hadrien and Baugh, Matthew and Kainz, Bernhard},
  booktitle={Proceedings of the IEEE/CVF International Conference on Computer Vision},
  pages={988--998},
  year={2023}
}
@inproceedings{tan2021detecting,
  title={Detecting outliers with poisson image interpolation},
  author={Tan, Jeremy and Hou, Benjamin and Day, Thomas and Simpson, John and Rueckert, Daniel and Kainz, Bernhard},
  booktitle={Medical Image Computing and Computer Assisted Intervention--MICCAI 2021: 24th International Conference, Strasbourg, France, September 27--October 1, 2021, Proceedings, Part V 24},
  pages={581--591},
  year={2021},
  organization={Springer}
}
@inproceedings{he2016deep,
  title={Deep residual learning for image recognition},
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  pages={770--778},
  year={2016}
}
@misc{hendrycks2020augmix,
      title={AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty}, 
      author={Dan Hendrycks and Norman Mu and Ekin D. Cubuk and Barret Zoph and Justin Gilmer and Balaji Lakshminarayanan},
      year={2020},
      eprint={1912.02781},
      archivePrefix={arXiv},
      primaryClass={stat.ML}
}
@inproceedings{wolleb2022diffusion,
  title={Diffusion models for medical anomaly detection},
  author={Wolleb, Julia and Bieder, Florentin and Sandk{\"u}hler, Robin and Cattin, Philippe C},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={35--45},
  year={2022},
  organization={Springer}
}
@article{chambon2022adapting,
  title={Adapting pretrained vision-language foundational models to medical imaging domains},
  author={Chambon, Pierre and Bluethgen, Christian and Langlotz, Curtis P and Chaudhari, Akshay},
  journal={arXiv preprint arXiv:2210.04133},
  year={2022}
}
@article{chen2023berdiff,
  title={BerDiff: Conditional Bernoulli Diffusion Model for Medical Image Segmentation},
  author={Chen, Tao and Wang, Chenhui and Shan, Hongming},
  journal={arXiv preprint arXiv:2304.04429},
  year={2023}
}
@inproceedings{zhou2023uxdiff,
  title={UXDiff: Synthesis of X-Ray Image from Ultrasound Coronal Image of Spine with Diffusion Probabilistic Network},
  author={Zhou, Yihao and Wu, Chonglin and Wang, Xinyi and Zheng, Yongping},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={3--12},
  year={2023},
  organization={Springer}
}
@inproceedings{wang2023medical,
  title={Medical Boundary Diffusion Model for Skin Lesion Segmentation},
  author={Wang, Jiacheng and Yang, Jing and Zhou, Qichao and Wang, Liansheng},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  pages={427--436},
  year={2023},
  organization={Springer}
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@article{somepalli2023understanding,
  title={Understanding and Mitigating Copying in Diffusion Models},
  author={Somepalli, Gowthami and Singla, Vasu and Goldblum, Micah and Geiping, Jonas and Goldstein, Tom},
  journal={arXiv preprint arXiv:2305.20086},
  year={2023}
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@article{packhauser2022deep,
  title={Deep learning-based patient re-identification is able to exploit the biometric nature of medical chest X-ray data},
  author={Packh{\"a}user, Kai and G{\"u}ndel, Sebastian and M{\"u}nster, Nicolas and Syben, Christopher and Christlein, Vincent and Maier, Andreas},
  journal={Scientific Reports},
  volume={12},
  number={1},
  pages={14851},
  year={2022},
  publisher={Nature Publishing Group UK London}
}
@inproceedings{sanchez2022healthy,
  title={What is healthy? generative counterfactual diffusion for lesion localization},
  author={Sanchez, Pedro and Kascenas, Antanas and Liu, Xiao and O’Neil, Alison Q and Tsaftaris, Sotirios A},
  booktitle={MICCAI Workshop on Deep Generative Models},
  pages={34--44},
  year={2022},
  organization={Springer}
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@article{ktena2024generative,
  title={Generative models improve fairness of medical classifiers under distribution shifts},
  author={Ktena, Ira and Wiles, Olivia and Albuquerque, Isabela and Rebuffi, Sylvestre-Alvise and Tanno, Ryutaro and Roy, Abhijit Guha and Azizi, Shekoofeh and Belgrave, Danielle and Kohli, Pushmeet and Cemgil, Taylan and others},
  journal={Nature Medicine},
  pages={1--8},
  year={2024},
  publisher={Nature Publishing Group US New York}
}

@inproceedings{khan2023fair,
  title={How Fair are Medical Imaging Foundation Models?},
  author={Khan, Muhammad Osama and Afzal, Muhammad Muneeb and Mirza, Shujaat and Fang, Yi},
  booktitle={Machine Learning for Health (ML4H)},
  pages={217--231},
  year={2023},
  organization={PMLR}
}
@misc{jin2024fairmedfmfairnessbenchmarkingmedical,
      title={FairMedFM: Fairness Benchmarking for Medical Imaging Foundation Models}, 
      author={Ruinan Jin and Zikang Xu and Yuan Zhong and Qiongsong Yao and Qi Dou and S. Kevin Zhou and Xiaoxiao Li},
      year={2024},
      eprint={2407.00983},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/2407.00983}, 
}
