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Diffusion models (DMs) have recently gained attention with state-of-the-art performance in text-to-image synthesis.
A mathematical theory of communication
C. E. Shannon · 1948
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2014
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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What does attention in neural machine translation pay attention to?
Hamidreza Ghader and Christof Monz · 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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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Generating wikipedia by summarizing long sequences
Peter J Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer · 2018
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Image transformer
Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran · 2018
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Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
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Generating long sequences with sparse transformers
Rewon Child, Scott Gray, Alec Radford, and Ilya Sutskever · 2019
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Meta-sr: A magnification-arbitrary network for super-resolution
Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan, and Jian Sun · 2019
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A closed-form solution to universal style transfer
Ming Lu, Hao Zhao, Anbang Yao, Yurong Chen, Feng Xu, and Li Zhang · 2019
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Boundless: Generative adversarial networks for image extension
Piotr Teterwak, Aaron Sarna, Dilip Krishnan, Aaron Maschinot, David Belanger, Ce Liu, and William T Freeman · 2019
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Very long natural scenery image prediction by outpainting
Zongxin Yang, Jian Dong, Ping Liu, Yi Yang, and Shuicheng Yan · 2019
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Etc: Encoding long and structured inputs in transformers
Joshua Ainslie, Santiago Ontanon, Chris Alberti, Vaclav Cvicek, Zachary Fisher, Philip Pham, Anirudh Ravula, Sumit Sanghai, Qifan Wang, and Li Yang · 2020
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Longformer: The long-document transformer
Iz Beltagy, Matthew E Peters, and Arman Cohan · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Reformer: The efficient transformer
Nikita Kitaev, Łukasz Kaiser, and Anselm Levskaya · 2020
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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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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 · 2020
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Sparse sinkhorn attention
Yi Tay, Dara Bahri, Liu Yang, Donald Metzler, and Da-Cheng Juan · 2020
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Fast transformers with clustered attention
Apoorv Vyas, Angelos Katharopoulos, and François Fleuret · 2020
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Big bird: Transformers for longer sequences
Manzil Zaheer, Guru Guruganesh, Kumar Avinava Dubey, Joshua Ainslie, Chris Alberti, Santiago Ontanon, Philip Pham, Anirudh Ravula, Qifan Wang, Li Yang, et al · 2020
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Learning continuous image representation with local implicit image function
Yinbo Chen, Sifei Liu, and Xiaolong Wang · 2021
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Pixelated butterfly: Simple and efficient sparse training for neural network models
Tri Dao, Beidi Chen, Kaizhao Liang, Jiaming Yang, Zhao Song, Atri Rudra, and Christopher Re · 2021
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Cascaded diffusion models for high fidelity image generation
Jonathan Ho, Chitwan Saharia, William Chan, David J Fleet, Mohammad Norouzi, and Tim Salimans · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, and Behnam Neyshabur · 2022
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Style spectroscope: Improve interpretability and controllability through fourier analysis
Zhiyu Jin, Xuli Shen, Bin Li, and Xiangyang Xue · 2022
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Elucidating the design space of diffusion-based generative models
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Boosting image outpainting with semantic layout prediction
Ye Ma, Jin Ma, Min Zhou, Quan Chen, Tiezheng Ge, Yuning Jiang, and Tong Lin · 2021
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Sdedit: Guided image synthesis and editing with stochastic differential equations
Chenlin Meng, Yutong He, Yang Song, Jiaming Song, Jiajun Wu, Jun-Yan Zhu, and Stefano Ermon · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Efficient content-based sparse attention with routing transformers
Aurko Roy, Mohammad Saffar, Ashish Vaswani, and David Grangier · 2021
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Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
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Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Krzysztof Lis, Matthias Rottmann, Sina Honari, Pascal Fua, and Mathieu Salzmann · 2022
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Repaint: Inpainting using denoising diffusion probabilistic models
Andreas Lugmayr, Martin Danelljan, Andres Romero, Fisher Yu, Radu Timofte, and Luc Van Gool · 2022
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Treeformer: Dense gradient trees for efficient attention computation
Lovish Madaan, Srinadh Bhojanapalli, Himanshu Jain, and Prateek Jain · 2022
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Byung-Doh Oh and William Schuler · 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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Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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What dense graph do you need for self-attention?
Yuxin Wang, Chu-Tak Lee, Qipeng Guo, Zhangyue Yin, Yunhua Zhou, Xuanjing Huang, and Xipeng Qiu · 2022
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Smartbrush: Text and shape guided object inpainting with diffusion model
Shaoan Xie, Zhifei Zhang, Zhe Lin, Tobias Hinz, and Kun Zhang · 2022
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Multidiffusion: Fusing diffusion paths for controlled image generation
Omer Bar-Tal, Lior Yariv, Yaron Lipman, and Tali Dekel · 2023
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Active visual exploration based on attention-map entropy
Adam Pardyl, Grzegorz Rypeść, Grzegorz Kurzejamski, Bartosz Zieliński, and Tomasz Trzciński · 2023
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Compositional scene representation learning via reconstruction: A survey
Jinyang Yuan, Tonglin Chen, Bin Li, and Xiangyang Xue · 2023
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