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In recent years, diffusion models have achieved tremendous success in the field of image generation, becoming the stateof-the-art technology for AI-based image processing applications.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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Learning multiple layers of features from tiny images
A. Krizhevsky · 2009
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The algorithmic foundations of differential privacy
C. Dwork, A. Roth, et al · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2014
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Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
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Deep learning face attributes in the wild
Z. Liu, P. Luo, X. Wang, and X. Tang · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
J. Sohl-Dickstein, E. Weiss, N. Maheswaranathan, and S. Ganguli · 2015
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Deep learning with differential privacy
M. Abadi, A. Chu, I. Goodfellow, H. B. McMahan, I. Mironov, K. Talwar, and L. Zhang · 2016
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GANs trained by a two time-scale update rule converge to a local nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
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Membership inference attacks against machine learning models
R. Shokri, M. Stronati, C. Song, and V. Shmatikov · 2017
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Privacy risk in machine learning: Analyzing the connection to overfitting
S. Yeom, I. Giacomelli, M. Fredrikson, and S. Jha · 2018
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Logan: Membership inference attacks against generative models
J. Hayes, L. Melis, G. Danezis, and E. De Cristofaro · 2019
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Monte Carlo and reconstruction membership inference attacks against generative models
B. Hilprecht, M. Härterich, and D. Bernau · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
Cited alongside, same era.
Comprehensive privacy analysis of deep learning: Passive and active white-box inference attacks against centralized and federated learning
M. Nasr, R. Shokri, and A. Houmansadr · 2019
Cited alongside, same era.
White-box vs black-box: Bayes optimal strategies for membership inference
A. Sablayrolles, M. Douze, Y. Ollivier, C. Schmid, and H. Jégou · 2019
Cited alongside, same era.
ML-Leaks: Model and data independent membership inference attacks and defenses on machine learning models
A. Salem, Y. Zhang, M. Humbert, M. Fritz, and M. Backes · 2019
Cited alongside, same era.
Systematic evaluation of privacy risks of machine learning models
L. Song and P. Mittal · 2021
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Membership inference attacks from first principles
N. Carlini, S. Chien, M. Nasr, S. Song, A. Terzis, and F. Tramer · 2022
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Differentially private diffusion models
T. Dockhorn, T. Cao, A. Vahdat, and K. Kreis · 2022
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Hierarchical text-conditional image generation with CLIP latents
A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Generative modeling by estimating gradients of the data distribution
Y. Song and S. Ermon · 2019
Cited alongside, same era.
Gan-leaks: A taxonomy of membership inference attacks against generative models
D. Chen, N. Yu, Y. Zhang, and M. Fritz · 2020
Cited alongside, same era.
Denoising diffusion probabilistic models
J. Ho, A. Jain, and P. Abbeel · 2020
Cited alongside, same era.
Towards the infeasibility of membership inference on deep models
S. Rezaei and X. Liu · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Y. Song and S. Ermon · 2020
Cited alongside, same era.
Diffusion models beat GANs on image synthesis
P. Dhariwal and A. Nichol · 2021
Cited alongside, same era.
Variational diffusion models
D. Kingma, T. Salimans, B. Poole, and J. Ho · 2021
Cited alongside, same era.
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
C. Saharia, W. Chan, S. Saxena, L. Li, J. Whang, E. Denton, S. K. S. Ghasemipour, B. K. Ayan, S. S. Mahdavi, R. G. Lopes, et al · 2022
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Membership inference attacks against text-to-image generation models
Y. Wu, N. Yu, Z. Li, M. Backes, and Y. Zhang · 2022
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Extracting training data from diffusion models
N. Carlini, J. Hayes, M. Nasr, M. Jagielski, V. Sehwag, F. Tramer, B. Balle, D. Ippolito, and E. Wallace · 2023
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Are diffusion models vulnerable to membership inference attacks?
J. Duan, F. Kong, S. Wang, X. Shi, and K. Xu · 2023
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Membership inference of diffusion models
H. Hu and J. Pang · 2023
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An efficient membership inference attack for the diffusion model by proximal initialization
F. Kong, J. Duan, R. Ma, H. Shen, X. Zhu, X. Shi, and K. Xu · 2023
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Membership inference attacks against diffusion models
T. Matsumoto, T. Miura, and N. Yanai · 2023
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