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Diffusion models have rapidly become a vital part of deep generative architectures, given today's increasing demands.
Learning algorithms for classification: A comparison on handwritten digit recognition
Yann LeCun, Lawrence D Jackel, Léon Bottou, Corinna Cortes, John S Denker, Harris Drucker, Isabelle Guyon, Urs A Muller, Eduard Sackinger, Patrice Simard, et al · 1995
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2014
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Deep learning face attributes in the wild
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric A. Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Improved techniques for training gans
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Embedding watermarks into deep neural networks
Yusuke Uchida, Yuki Nagai, Shigeyuki Sakazawa, and Shin’ichi Satoh · 2017
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Neural discrete representation learning
Aäron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Turning your weakness into a strength: Watermarking deep neural networks by backdooring
Yossi Adi, Carsten Baum, Moustapha Cissé, Benny Pinkas, and Joseph Keshet · 2018
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Watermarking deep neural networks for embedded systems
Jia Guo and Miodrag Potkonjak · 2018
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Protecting intellectual property of deep neural networks with watermarking
Jialong Zhang, Zhongshu Gu, Jiyong Jang, Hui Wu, Marc Ph. Stoecklin, Heqing Huang, and Ian M. Molloy · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Deepmarks: A secure fingerprinting framework for digital rights management of deep learning models
Huili Chen, Bita Darvish Rouhani, Cheng Fu, Jishen Zhao, and Farinaz Koushanfar · 2019
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How to prove your model belongs to you: a blind-watermark based framework to protect intellectual property of DNN
Zheng Li, Chengyu Hu, Yang Zhang, and Shanqing Guo · 2019
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Robust watermarking of neural network with exponential weighting
Ryota Namba and Jun Sakuma · 2019
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Deepsigns: An end-to-end watermarking framework for ownership protection of deep neural networks
Bita Darvish Rouhani, Huili Chen, and Farinaz Koushanfar · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Generative adversarial networks
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2020
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Denoising diffusion probabilistic models
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2021
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DAWN: dynamic adversarial watermarking of neural networks
Sebastian Szyller, Buse Gul Atli, Samuel Marchal, and N. Asokan · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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RIGA: covert and robust white-box watermarking of deep neural networks
Tianhao Wang and Florian Kerschbaum · 2021
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Robust watermarking for deep neural networks via bi-level optimization
Peng Yang, Yingjie Lao, and Ping Li · 2021
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Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Adversarial frontier stitching for remote neural network watermarking
Erwan Le Merrer, Patrick Pérez, and Gilles Trédan · 2020
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Quinn Nichol · 2021
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Entangled watermarks as a defense against model extraction
Hengrui Jia, Christopher A. Choquette-Choo, Varun Chandrasekaran, and Nicolas Papernot · 2021
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A survey of deep neural network watermarking techniques
Yue Li, Hongxia Wang, and Mauro Barni · 2021
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Watermarking deep neural networks with greedy residuals
Hanwen Liu, Zhenyu Weng, and Yuesheng Zhu · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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Artificial fingerprinting for generative models: Rooting deepfake attribution in training data
Ning Yu, Vladislav Skripniuk, Sahar Abdelnabi, and Mario Fritz · 2021
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How to backdoor diffusion models?
Sheng-Yen Chou, Pin-Yu Chen, and Tsung-Yi Ho · 2022
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Supervised GAN watermarking for intellectual property protection
Jianwei Fei, Zhihua Xia, Benedetta Tondi, and Mauro Barni · 2022
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Intellectual property protection of dnn models
Sen Peng, Yufei Chen, Jie Xu, Zizhuo Chen, Cong Wang, and Xiaohua Jia · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Trojdiff: Trojan attacks on diffusion models with diverse targets
Weixin Chen, Dawn Song, and Bo Li · 2023
Closest in time.
Yugeng Liu, Zheng Li, Michael Backes, Yun Shen, and Yang Zhang · 2023
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A recipe for watermarking diffusion models
Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Ngai-Man Cheung, and Min Lin · 2023
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