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Diffusion models, emerging as powerful deep generative tools, excel in various applications.
“Towards practical plug-and-play diffusion models”
Hyojun Go, Yunsung Lee, Jin-Young Kim, Seunghyun Lee, Myeongho Jeong, Hyun Lee and Seungtaek Choi · 1971
Earlier work this paper cites.
“Learning multiple layers of features from tiny images”
Alex Krizhevsky and Geoffrey Hinton · 2009
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“A connection between score matching and denoising autoencoders”
Pascal Vincent · 2011
Earlier work this paper cites.
“Deep Learning Face Attributes in the Wild”
Ziwei Liu, Ping Luo, Xiaogang Wang and Xiaoou Tang · 2015
Earlier work this paper cites.
“U-net: Convolutional networks for biomedical image segmentation”
Olaf Ronneberger, Philipp Fischer and Thomas Brox · 2015
Earlier work this paper cites.
“Mask r-cnn”
Kaiming He, Georgia Gkioxari, Piotr Dollár and Ross Girshick · 2017
Earlier work this paper cites.
“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
Earlier work this paper cites.
“Denoising diffusion probabilistic models”
Jonathan Ho, Ajay Jain and Pieter Abbeel · 2020
Earlier work this paper cites.
“High-fidelity performance metrics for generative models in PyTorch” Version: 0.2.0, DOI: 10.5281/zenodo.3786540
Anton Obukhov, Maximilian Seitzer, Po-Wei Wu, Semen Zhydenko, Jonathan Kyl and Elvis-Jing Lin · 2020
Earlier work this paper cites.
“Denoising diffusion implicit models”
Jiaming Song, Chenlin Meng and Stefano Ermon · 2020
Earlier work this paper cites.
“Score-based generative modeling through stochastic differential equations”
Yang Song, Jascha Sohl-Dickstein, Diederik Kingma, Abhishek Kumar, Stefano Ermon and Ben Poole · 2020
Earlier work this paper cites.
“Diffusion models beat gans on image synthesis”
Prafulla Dhariwal and Alexander Nichol · 2021
Earlier work this paper cites.
“Glide: Towards photorealistic image generation and editing with text-guided diffusion models”
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever and Mark Chen · 2021
Earlier work this paper cites.
“Zero-shot text-to-image generation”
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen and Ilya Sutskever · 2021
Cited alongside, same era.
“Solving inverse problems in medical imaging with score-based generative models”
Yang Song, Liyue Shen, Lei Xing and Stefano Ermon · 2021
Cited alongside, same era.
“ediffi: Text-to-image diffusion models with an ensemble of expert denoisers”
Yogesh Balaji, Seungjun Nah, Xun Huang, Arash Vahdat, Jiaming Song, Karsten Kreis, Miika Aittala, Timo Aila, Samuli Laine and Bryan Catanzaro · 2022
Cited alongside, same era.
“Perception prioritized training of diffusion models”
Jooyoung Choi, Jungbeom Lee, Chaehun Shin, Sungwon Kim, Hyunwoo Kim and Sungroh Yoon · 2022
Cited alongside, same era.
“Diffusion posterior sampling for general noisy inverse problems”
Hyungjin Chung, Jeongsol Kim, Michael Mccann, Marc Klasky and Jong Ye · 2022
“Dual diffusion implicit bridges for image-to-image translation”
Xuan Su, Jiaming Song, Chenlin Meng and Stefano Ermon · 2022
Later among the works it cites.
“Poisson flow generative models”
Yilun Xu, Ziming Liu, Max Tegmark and Tommi Jaakkola · 2022
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“Fast Sampling of Diffusion Models with Exponential Integrator”
Qinsheng Zhang and Yongxin Chen · 2022
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“Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations”
Min Zhao, Fan Bao, Chongxuan Li and Jun Zhu · 2022
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“gDDIM: Generalized denoising diffusion implicit models”
Qinsheng Zhang, Molei Tao and Yongxin Chen · 2022
Later among the works it cites.
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Cited alongside, same era.
“Flexible diffusion modeling of long videos”
William Harvey, Saeid Naderiparizi, Vaden Masrani, Christian Weilbach and Frank Wood · 2022
Cited alongside, same era.
“Imagen video: High definition video generation with diffusion models”
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey Gritsenko, Diederik Kingma, Ben Poole, Mohammad Norouzi and David Fleet · 2022
Cited alongside, same era.
“Classifier-free diffusion guidance”
Jonathan Ho and Tim Salimans · 2022
Cited alongside, same era.
“Elucidating the design space of diffusion-based generative models”
Tero Karras, Miika Aittala, Timo Aila and Samuli Laine · 2022
Cited alongside, same era.
“Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps”
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li and Jun Zhu · 2022
Cited alongside, same era.
“High-resolution image synthesis with latent diffusion models”
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser and Björn Ommer · 2022
Cited alongside, same era.
“Palette: Image-to-image diffusion models”
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet and Mohammad Norouzi · 2022
Cited alongside, same era.
“Diffusion-based Adversarial Purification for Robust Deep MRI Reconstruction”
Ismail Alkhouri, Shijun Liang, Rongrong Wang, Qing Qu and Saiprasad Ravishankar · 2023
Closest in time.
“Addressing Negative Transfer in Diffusion Models”
Hyojun Go, JinYoung Kim, Yunsung Lee, Seunghyun Lee, Shinhyeok Oh, Hyeongdon Moon and Seungtaek Choi · 2023
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“Multi-Architecture Multi-Expert Diffusion Models”
Yunsung Lee, Jin-Young Kim, Hyojun Go, Myeongho Jeong, Shinhyeok Oh and Seungtaek Choi · 2023
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“Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency”
Bowen Song, Soo Kwon, Zecheng Zhang, Xinyu Hu, Qing Qu and Liyue Shen · 2023
Closest in time.
“Consistency models”, 2023
Yang Song, Prafulla Dhariwal, Mark Chen and Ilya Sutskever · 2023
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“ { \{ SkyPilot } \} : An Intercloud Broker for Sky Computing”
Zongheng Yang, Zhanghao Wu, Michael Luo, Wei-Lin Chiang, Romil Bhardwaj, Woosuk Kwon, Siyuan Zhuang, Frank Luan, Gautam Mittal and Scott Shenker · 2023
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“The emergence of reproducibility and consistency in diffusion models”
Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Liyue Shen and Qing Qu · 2023
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