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Generative modeling has recently undergone remarkable advancements, primarily propelled by the transformative implications of Diffusion Probabilistic Models (DPMs).
Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli · 2004
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Higher-order derivatives and taylor’s formula in several variables
Gerald B Folland · 2005
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Ari Seff, Yinda Zhang, Shuran Song, Thomas Funkhouser, and Jianxiong Xiao · 2015
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Pruning filters for efficient convnets
Hao Li, Asim Kadav, Igor Durdanovic, Hanan Samet, and Hans Peter Graf · 2016
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Learning to prune deep neural networks via layer-wise optimal brain surgeon
Xin Dong, Shangyu Chen, and Sinno Pan · 2017
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Channel pruning for accelerating very deep neural networks
Yihui He, Xiangyu Zhang, and Jian Sun · 2017
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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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Learning efficient convolutional networks through network slimming
Zhuang Liu, Jianguo Li, Zhiqiang Shen, Gao Huang, Shoumeng Yan, and Changshui Zhang · 2017
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Thinet: A filter level pruning method for deep neural network compression
Jian-Hao Luo, Jianxin Wu, and Weiyao Lin · 2017
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The lottery ticket hypothesis: Finding sparse, trainable neural networks
Jonathan Frankle and Michael Carbin · 2018
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Amc: Automl for model compression and acceleration on mobile devices
Yihui He, Ji Lin, Zhijian Liu, Hanrui Wang, Li-Jia Li, and Song Han · 2018
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Large-scale celebfaces attributes (celeba) dataset
Ziwei Liu, Ping Luo, Xiaogang Wang, and Xiaoou Tang · 2018
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Rethinking the smaller-norm-less-informative assumption in channel pruning of convolution layers
Jianbo Ye, Xin Lu, Zhe Lin, and James Z Wang · 2018
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Centripetal sgd for pruning very deep convolutional networks with complicated structure
Xiaohan Ding, Guiguang Ding, Yuchen Guo, and Jungong Han · 2019
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Filter pruning via geometric median for deep convolutional neural networks acceleration
Yang He, Ping Liu, Ziwei Wang, Zhilan Hu, and Yi Yang · 2019
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A signal propagation perspective for pruning neural networks at initialization
Namhoon Lee, Thalaiyasingam Ajanthan, Stephen Gould, and Philip HS Torr · 2019
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Importance estimation for neural network pruning
Pavlo Molchanov, Arun Mallya, Stephen Tyree, Iuri Frosio, and Jan Kautz · 2019
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Gate decorator: Global filter pruning method for accelerating deep convolutional neural networks
Zhonghui You, Kun Yan, Jinmian Ye, Meng Ma, and Ping Wang · 2019
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Towards efficient model compression via learned global ranking
Ting-Wu Chin, Ruizhou Ding, Cha Zhang, and Diana Marculescu · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Gan compression: Efficient architectures for interactive conditional gans
Muyang Li, Ji Lin, Yaoyao Ding, Zhijian Liu, Jun-Yan Zhu, and Song Han · 2020
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Lookahead: a far-sighted alternative of magnitude-based pruning
Accelerating diffusion models via early stop of the diffusion process
Zhaoyang Lyu, Xudong Xu, Ceyuan Yang, Dahua Lin, and Bo Dai · 2022
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Wavelet diffusion models are fast and scalable image generators
Hao Phung, Quan Dao, and Anh Tran · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 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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Progressive distillation for fast sampling of diffusion models
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Sejun Park, Jaeho Lee, Sangwoo Mo, and Jinwoo Shin · 2020
Cited alongside, same era.
Movement pruning: Adaptive sparsity by fine-tuning
Victor Sanh, Thomas Wolf, and Alexander Rush · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Segdiff: Image segmentation with diffusion probabilistic models
Tomer Amit, Tal Shaharbany, Eliya Nachmani, and Lior Wolf · 2021
Cited alongside, same era.
Cap: Context-aware pruning for semantic segmentation
Wei He, Meiqing Wu, Mingfu Liang, and Siew-Kei Lam · 2021
Cited alongside, same era.
Group fisher pruning for practical network compression
Liyang Liu, Shilong Zhang, Zhanghui Kuang, Aojun Zhou, Jing-Hao Xue, Xinjiang Wang, Yimin Chen, Wenming Yang, Qingmin Liao, and Wayne Zhang · 2021
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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Tim Salimans and Jonathan Ho · 2022
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Ppcd-gan: Progressive pruning and class-aware distillation for large-scale conditional gans compression
Duc Minh Vo, Akihiro Sugimoto, and Hideki Nakayama · 2022
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Diffusers: State-of-the-art diffusion models
Patrick von Platen, Suraj Patil, Anton Lozhkov, Pedro Cuenca, Nathan Lambert, Kashif Rasul, Mishig Davaadorj, and Thomas Wolf · 2022
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Diffusion probabilistic model made slim
Xingyi Yang, Daquan Zhou, Jiashi Feng, and Xinchao Wang · 2022
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Towards automatic neural architecture search within general super-networks
Tianyi Chen, Luming Liang, Tianyu Ding, and Ilya Zharkov · 2023
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Otov2: Automatic, generic, user-friendly
Tianyi Chen, Luming Liang, Tianyu Ding, Zhihui Zhu, and Ilya Zharkov · 2023
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Depgraph: Towards any structural pruning
Gongfan Fang, Xinyin Ma, Mingli Song, Michael Bi Mi, and Xinchao Wang · 2023
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Efficient diffusion training via min-snr weighting strategy
Tiankai Hang, Shuyang Gu, Chen Li, Jianmin Bao, Dong Chen, Han Hu, Xin Geng, and Baining Guo · 2023
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Oms-dpm: Optimizing the model schedule for diffusion probabilistic models
En hao Liu, Xuefei Ning, Zi-Han Lin, Huazhong Yang, and Yu Wang · 2023
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Efficient Representation Learning With Graph Neural Networks
Yongcheng Jing · 2023
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Patch diffusion: Faster and more data-efficient training of diffusion models
Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, and Mingyuan Zhou · 2023
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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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A survey on model compression for large language models
Xunyu Zhu, Jian Li, Yong Liu, Can Ma, and Weiping Wang · 2023
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