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In diffusion models, UNet is the most popular network backbone, since its long skip connects (LSCs) to connect distant network blocks can aggregate long-distant information and alleviate vanishing gradient.
Numerical inversion of a characteristic function
Robert B Davies · 1973
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Algorithm as 155: The distribution of a linear combination of
Robert B Davies · 1980
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
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Survey of simple, continuous, univariate probability distributions
Gavin E Crooks · 2012
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Imagenet large scale visual recognition challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael S. Bernstein, Alexander C. Berg, and Li Fei-Fei · 2014
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Microsoft coco: Common objects in context
Tsung-Yi Lin, Michael Maire, Serge J. Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C. Lawrence Zitnick · 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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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Fast and accurate deep network learning by exponential linear units (elus)
Djork-Arné Clevert, Thomas Unterthiner, and Sepp Hochreiter · 2015
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Tim Cooijmans, Nicolas Ballas, César Laurent, and Aaron C. Courville · 2016
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Memnet: A persistent memory network for image restoration
Ying Tai, Jian Yang, Xiaoming Liu, and Chunyan Xu · 2017
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The shattered gradients problem: If resnets are the answer, then what is the question?
David Balduzzi, Marcus Frean, Lennox Leary, JP Lewis, Kurt Wan-Duo Ma, and Brian McWilliams · 2017
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Squeeze-and-excitation networks
Jie Hu, Li Shen, Samuel Albanie, Gang Sun, and Enhua Wu · 2017
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2018
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How to start training: The effect of initialization and architecture
Boris Hanin and David Rolnick · 2018
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How does batch normalization help optimization? (no, it is not about internal covariate shift)
Shibani Santurkar, Dimitris Tsipras, Andrew Ilyas, and Aleksander Madry · 2018
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Glow: Generative flow with invertible 1x1 convolutions
Diederik P. Kingma and Prafulla Dhariwal · 2018
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Deep learning using rectified linear units (relu)
Abien Fred Agarap · 2018
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Cbam: Convolutional block attention module
Sanghyun Woo, Jongchan Park, Joon-Young Lee, and In-So Kweon · 2018
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Infovae: Balancing learning and inference in variational autoencoders
Shengjia Zhao, Jiaming Song, and Stefano Ermon · 2019
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Stabilize deep resnet with a sharp scaling factor tau
Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, and Tie-Yan Liu · 2019
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Fixup initialization: Residual learning without normalization
Hongyi Zhang, Yann Dauphin, and Tengyu Ma · 2019
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Instance enhancement batch normalization: an adaptive regulator of batch noise
Senwei Liang, Zhongzhan Huang, Mingfu Liang, and Haizhao Yang · 2019
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Dianet: Dense-and-implicit attention network
Zhongzhan Huang, Senwei Liang, Mingfu Liang, and Haizhao Yang · 2019
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A convergence theory for deep learning via over-parameterization
Zeyuan Allen-Zhu, Yuanzhi Li, and Zhao Song · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Narain Sohl-Dickstein, Diederik P. Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and P. Abbeel · 2020
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Rezero is all you need: Fast convergence at large depth
Thomas C. Bachlechner, Bodhisattwa Prasad Majumder, Huanru Henry Mao, G. Cottrell, and Julian McAuley · 2020
Cited alongside, same era.
Batch normalization biases residual blocks towards the identity function in deep networks
Soham De and Samuel L. Smith · 2020
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On layer normalization in the transformer architecture, 2020
Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Huishuai Zhang, Yanyan Lan, Liwei Wang, and Tie-Yan Liu · 2020
Cited alongside, same era.
Stable resnet
Soufiane Hayou, Eugenio Clerico, Bo He, George Deligiannidis, A. Doucet, and Judith Rousseau · 2020
Cited alongside, same era.
Revisiting internal covariate shift for batch normalization
Muhammad Awais, Md. Tauhid Bin Iqbal, and Sung-Ho Bae · 2020
Cited alongside, same era.
An internal covariate shift bounding algorithm for deep neural networks by unitizing layers’ outputs
Rodin: A generative model for sculpting 3d digital avatars using diffusion
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, et al · 2022
Later among the works it cites.
Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou, Jianzhuang Liu, and Houqiang Li · 2022
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Restormer: Efficient transformer for high-resolution image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
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Simple baselines for image restoration
Liangyu Chen, Xiaojie Chu, Xiangyu Zhang, and Jian Sun · 2022
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You Huang and Yuanlong Yu · 2020
Cited alongside, same era.
Long-tailed recognition by routing diverse distribution-aware experts
Xudong Wang, Long Lian, Zhongqi Miao, Ziwei Liu, and Stella X. Yu · 2020
Cited alongside, same era.
Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
Cited alongside, same era.
Mish: A self regularized non-monotonic activation function
Diganta Misra · 2020
Cited alongside, same era.
Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
Cited alongside, same era.
Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg · 2021
Cited alongside, same era.
Ilvr: Conditioning method for denoising diffusion probabilistic models
Jooyoung Choi, Sungwon Kim, Yonghyun Jeong, Youngjune Gwon, and Sungroh Yoon · 2021
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, Seyedeh Sara Mahdavi, Raphael Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, and Mohammad Norouzi · 2022
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All are worth words: a vit backbone for score-based diffusion models
Fan Bao, Chongxuan Li, Yue Cao, and Jun Zhu · 2022
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Classifier-free diffusion guidance
Jonathan Ho · 2022
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2022
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Multi-concept customization of text-to-image diffusion
Nupur Kumari, Bin Zhang, Richard Zhang, Eli Shechtman, and Jun-Yan Zhu · 2022
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Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models
Jiale Xu, Xintao Wang, Weihao Cheng, Yan-Pei Cao, Ying Shan, Xiaohu Qie, and Shenghua Gao · 2022
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Denoising diffusion probabilistic models for 3d medical image generation
Firas Khader, Gustav Mueller-Franzes, Soroosh Tayebi Arasteh, Tianyu Han, Christoph Haarburger, Maximilian Franz Schulze-Hagen, Philipp Schad, Sandy Engelhardt, Bettina Baessler, Sebastian Foersch, J. Stegmaier, Christiane Kuhl, Sven Nebelung, Jakob Nikolas Kather, and Daniel Truhn · 2022
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Imbalance fault diagnosis under long-tailed distribution: Challenges, solutions and prospects
Zhuo Chen, Jinglong Chen, Yong Feng, Shen Liu, Tianci Zhang, Kaiyu Zhang, and Wenrong Xiao · 2022
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Long- tailed recognition via weight balancing
Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan, and Shu Kong · 2022
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Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Your vit is secretly a hybrid discriminative-generative diffusion model
Xiulong Yang, Sheng-Min Shih, Yinlin Fu, Xiaoting Zhao, and Shihao Ji · 2022
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Frido: Feature pyramid diffusion for complex scene image synthesis
Wanshu Fan, Yen-Chun Chen, Dongdong Chen, Yu Cheng, Lu Yuan, and Yu-Chiang Frank Wang · 2022
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Switchable self-attention module
Shan Zhong, Wushao Wen, and Jinghui Qin · 2022
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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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Diffusion models in vision: A survey
Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, and Mubarak Shah · 2023
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Masked diffusion transformer is a strong image synthesizer
Shanghua Gao, Pan Zhou, Ming-Ming Cheng, and Shuicheng Yan · 2023
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Dreamix: Video diffusion models are general video editors
Eyal Molad, Eliahu Horwitz, Dani Valevski, Alex Rav Acha, Yossi Matias, Yael Pritch, Yaniv Leviathan, and Yedid Hoshen · 2023
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Structure and content-guided video synthesis with diffusion models
Patrick Esser, Johnathan Chiu, Parmida Atighehchian, Jonathan Granskog, and Anastasis Germanidis · 2023
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Align your latents: High-resolution video synthesis with latent diffusion models
Andreas Blattmann, Robin Rombach, Huan Ling, Tim Dockhorn, Seung Wook Kim, Sanja Fidler, and Karsten Kreis · 2023
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Kbnet: Kernel basis network for image restoration
Yi Zhang, Dasong Li, Xiaoyu Shi, Dailan He, Kangning Song, Xiaogang Wang, Hongwei Qin, and Hongsheng Li · 2023
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Sur-adapter: Enhancing text-to-image pre-trained diffusion models with large language models
Shanshan Zhong, Zhongzhan Huang, Wushao Wen, Jinghui Qin, and Liang Lin · 2023
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Deep transformers without shortcuts: Modifying self-attention for faithful signal propagation
Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andy Brock, Samuel L. Smith, and Yee Whye Teh · 2023
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One transformer fits all distributions in multi-modal diffusion at scale
Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shiliang Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, and Jun Zhu · 2023
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Diffusion models and semi-supervised learners benefit mutually with few labels
Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, and Jun Zhu · 2023
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