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Diffusion models have achieved great success in image generation tasks.
Post-training quantization on diffusion models
Shang, Y.; Yuan, Z.; Xie, B.; Wu, B.; and Yan, Y. 2023 · 1981
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Deng, J.; Dong, W.; Socher, R.; Li, L.-J.; Li, K.; and Fei-Fei, L. 2009 · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
Krizhevsky, A.; Hinton, G.; et al. 2009 · 2009
Earlier work this paper cites.
Denoising diffusion implicit models
Song, J.; Meng, C.; and Ermon, S. 2020 · 2010
Earlier work this paper cites.
Microsoft coco: Common objects in context
Lin, T.-Y.; Maire, M.; Belongie, S.; Hays, J.; Perona, P.; Ramanan, D.; Dollár, P.; and Zitnick, C. L. 2014 · 2014
Earlier work this paper cites.
U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O.; Fischer, P.; and Brox, T. 2015 · 2015
Earlier work this paper cites.
Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Yu, F.; Seff, A.; Zhang, Y.; Song, S.; Funkhouser, T.; and Xiao, J. 2015 · 2015
Earlier work this paper cites.
Improved techniques for training gans
Salimans, T.; Goodfellow, I.; Zaremba, W.; Cheung, V.; Radford, A.; and Chen, X. 2016 · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2017 · 2017
Earlier work this paper cites.
Accelerating image classification using feature map similarity in convolutional neural networks
Park, K.; and Kim, D.-H. 2018 · 2018
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Earlier work this paper cites.
Permutation invariant graph generation via score-based generative modeling
Niu, C.; Song, Y.; Song, J.; Zhao, S.; Grover, A.; and Ermon, S. 2020 · 2020
Earlier work this paper cites.
Image super-resolution reconstruction based on feature map attention mechanism
Chen, Y.; Liu, L.; Phonevilay, V.; Gu, K.; Xia, R.; Xie, J.; Zhang, Q.; and Yang, K. 2021 · 2021
Cited alongside, same era.
Clipscore: A reference-free evaluation metric for image captioning
Hessel, J.; Holtzman, A.; Forbes, M.; Bras, R. L.; and Choi, Y. 2021 · 2021
Cited alongside, same era.
Accurate post training quantization with small calibration sets
Hubara, I.; Nahshan, Y.; Hanani, Y.; Banner, R.; and Soudry, D. 2021 · 2021
Cited alongside, same era.
Brecq: Pushing the limit of post-training quantization by block reconstruction
Li, Y.; Gong, R.; Tan, X.; Yang, Y.; Hu, P.; Zhang, Q.; Yu, F.; Wang, W.; and Gu, S. 2021 · 2021
Cited alongside, same era.
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Learning fast samplers for diffusion models by differentiating through sample quality
Watson, D.; Chan, W.; Ho, J.; and Norouzi, M. 2022 · 2022
Later among the works it cites.
gDDIM: Generalized denoising diffusion implicit models
Zhang, Q.; Tao, M.; and Chen, Y. 2022 · 2022
Later among the works it cites.
I-vit: Integer-only quantization for efficient vision transformer inference
Li, Z.; and Gu, Q. 2023 · 2023
Later among the works it cites.
Unsupervised Medical Image Translation with Adversarial Diffusion Models
Ozbey, M.; Dalmaz, O.; Dar, S. U.; Bedel, H. A.; Ozturk, S.; Gungor, A.; and Cukur, T. 2023 · 2023
Later among the works it cites.
Wavelet diffusion models are fast and scalable image generators
Phung, H.; Dao, Q.; and Tran, A. 2023 · 2023
Later among the works it cites.
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Nichol, A.; Dhariwal, P.; Ramesh, A.; Shyam, P.; Mishkin, P.; McGrew, B.; Sutskever, I.; and Chen, M. 2021 · 2021
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Nichol, A. Q.; and Dhariwal, P. 2021 · 2021
Cited alongside, same era.
Rounding Shift Channel Post-Training Quantization using Layer Search
Xu, M.; Zhao, M.; Yu, S.; Zheng, X.; Wu, N.; and Liu, L. 2021 · 2021
Cited alongside, same era.
Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models
Lu, C.; Zhou, Y.; Bao, F.; Chen, J.; Li, C.; and Zhu, J. 2022 · 2022
Cited alongside, same era.
Repaint: Inpainting using denoising diffusion probabilistic models
Lugmayr, A.; Danelljan, M.; Romero, A.; Yu, F.; Timofte, R.; and Van Gool, L. 2022 · 2022
Cited alongside, same era.
High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C.; Chan, W.; Saxena, S.; Li, L.; Whang, J.; Denton, E. L.; Ghasemipour, K.; Gontijo Lopes, R.; Karagol Ayan, B.; Salimans, T.; et al. 2022 · 2022
Cited alongside, same era.
Efficientdm: Efficient quantization-aware fine-tuning of low-bit diffusion models
He, Y.; Liu, J.; Wu, W.; Zhou, H.; and Zhuang, B. 2023a
Cited in the paper.
So, J.; Lee, J.; Ahn, D.; Kim, H.; and Park, E. 2023 · 2023
Later among the works it cites.
Towards Accurate Data-free Quantization for Diffusion Models
Wang, C.; Wang, Z.; Xu, X.; Tang, Y.; Zhou, J.; and Lu, J. 2023 · 2023
Later among the works it cites.
Adding conditional control to text-to-image diffusion models
Zhang, L.; Rao, A.; and Agrawala, M. 2023 · 2023
Later among the works it cites.
Inversion-based style transfer with diffusion models
Zhang, Y.; Huang, N.; Tang, F.; Huang, H.; Ma, C.; Dong, W.; and Xu, C. 2023 · 2023
Later among the works it cites.
Deepcache: Accelerating diffusion models for free
Ma, X.; Fang, G.; and Wang, X. 2024 · 2024
Closest in time.
Temporal dynamic quantization for diffusion models
So, J.; Lee, J.; Ahn, D.; Kim, H.; and Park, E. 2024 · 2024
Closest in time.