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Latent diffusion models with Transformer architectures excel at generating high-fidelity images.
Visualizing data using t-sne
Laurens Van der Maaten and Geoffrey Hinton · 2008
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Auto-encoding variational bayes
Diederik P Kingma · 2013
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Deep residual learning for image recognition
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Neural discrete representation learning
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Root mean square layer normalization
Biao Zhang and Rico Sennrich · 2019
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Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick · 2021
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Earlier work this paper cites.
ibot: Image bert pre-training with online tokenizer
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Earlier work this paper cites.
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Huiwen Chang, Han Zhang, Lu Jiang, Ce Liu, and William T Freeman · 2022
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Intriguing properties of quantization at scale
Arash Ahmadian, Saurabh Dash, Hongyu Chen, Bharat Venkitesh, Zhen Stephen Gou, Phil Blunsom, Ahmet Üstün, and Sara Hooker · 2023
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Earlier work this paper cites.
Emu: Enhancing image generation models using photogenic needles in a haystack
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Segment anything
Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo, Zhiwu Lu, Ping Luo, and Mingyu Ding · 2023
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Maxime Oquab, Timothée Darcet, Theo Moutakanni, Huy V. Vo, Marc Szafraniec, Vasil Khalidov, Pierre Fernandez, Daniel Haziza, Francisco Massa, Alaaeldin El-Nouby, Russell Howes, Po-Yao Huang, Hu Xu, Vasu Sharma, Shang-Wen Li, Wojciech Galuba, Mike Rabbat, Mido Assran, Nicolas Ballas, Gabriel Synnaeve, Ishan Misra, Herve Jegou, Julien Mairal, Patrick Labatut, Armand Joulin, and Piotr Bojanowski · 2023
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William Peebles and Saining Xie · 2023
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Autoregressive image generation without vector quantization
Tianhong Li, Yonglong Tian, He Li, Mingyang Deng, and Kaiming He · 2024
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Playground v3: Improving text-to-image alignment with deep-fusion large language models
Bingchen Liu, Ehsan Akhgari, Alexander Visheratin, Aleks Kamko, Linmiao Xu, Shivam Shrirao, Joao Souza, Suhail Doshi, and Daiqing Li · 2024
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Sit: Exploring flow and diffusion-based generative models with scalable interpolant transformers
Nanye Ma, Mark Goldstein, Michael S Albergo, Nicholas M Boffi, Eric Vanden-Eijnden, and Saining Xie · 2024
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Sdxl: Improving latent diffusion models for high-resolution image synthesis
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Lijun Yu, José Lezama, Nitesh B Gundavarapu, Luca Versari, Kihyuk Sohn, David Minnen, Yong Cheng, Vighnesh Birodkar, Agrim Gupta, Xiuye Gu, et al · 2023
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Fal · 2024
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Torch Compile Tutorial
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Scaling the codebook size of vqgan to 100,000 with a utilization rate of 99%
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Photorealistic video generation with diffusion models
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