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There is a bias in the inference pipeline of most diffusion models.
Color and spatial structure in natural scenes
Geoffrey J Burton and Ian R Moorhead · 1987
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Relations between the statistics of natural images and the response properties of cortical cells
David J Field · 1987
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Amplitude spectra of natural images
David J Tolhurst, Yoav Tadmor, and Tang Chao · 1992
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Statistics of natural images: Scaling in the woods
Daniel L Ruderman and William Bialek · 1994
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2013
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba · 2015
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2015
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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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Generalization in Generation: A closer look at Exposure Bias
Florian Schmidt · 2019
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Stochastic frequency masking to improve super-resolution and denoising networks
Majed El Helou, Ruofan Zhou, and Sabine Süsstrunk · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2021
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LoRA: Low-Rank Adaptation of Large Language Models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 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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Improved denoising diffusion probabilistic models
Alexander Quinn Nichol and Prafulla Dhariwal · 2021
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Alexander Quinn Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob Mcgrew, Ilya Sutskever, and Mark Chen · 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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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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Denoising Diffusion Implicit Models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
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Progressive Distillation for Fast Sampling of Diffusion Models
Tim Salimans and Jonathan Ho · 2022
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LAION-Aesthetics, 2022
Christoph Schuhmann and Romain Beaumont · 2022
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GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
Minkai Xu, Lantao Yu, Yang Song, Chence Shi, Stefano Ermon, and Jian Tang · 2022
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ttj/flex-diffusion-2-1 — huggingface.co, 2023
Jonathan Chang · 2023
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Diffusion in Style
Martin Nicolas Everaert, Marco Bocchio, Sami Arpa, Sabine Süsstrunk, and Radhakrishna Achanta · 2023
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Diffusion with offset noise, 2023
Nicholas Guttenberg · 2023
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Dhruv Karan · 2022
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Pseudo Numerical Methods for Diffusion Models on Manifolds
Luping Liu, Yi Ren, Zhijie Lin, and Zhou Zhao · 2022
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Arbitrary style guidance for enhanced diffusion-based text-to-image generation
Zhihong Pan, Xin Zhou, and Hao Tian · 2022
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Pokemon BLIP captions, 2022
Justin N. M. Pinkney · 2022
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Mingxiao Li, Tingyu Qu, Wei Sun, and Marie-Francine Moens · 2023
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Common Diffusion Noise Schedules and Sample Steps are Flawed
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Input Perturbation Reduces Exposure Bias in Diffusion Models
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Shifted Diffusion for Text-to-image Generation
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